| program(1.3) |
| [buildInfo = dict<string, string>({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.22.1"}, {"coremltools-component-torch", "2.7.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})] |
| { |
| func main<ios18>(tensor<fp32, [1, 77]> input_ids) { |
| string cast_1_dtype_0 = const()[name = string("cast_1_dtype_0"), val = string("int32")]; |
| int32 inputs_embeds_batch_dims_0 = const()[name = string("inputs_embeds_batch_dims_0"), val = int32(0)]; |
| bool inputs_embeds_validate_indices_0 = const()[name = string("inputs_embeds_validate_indices_0"), val = bool(false)]; |
| tensor<fp16, [49408, 768]> text_encoder_text_model_embeddings_token_embedding_weight_to_fp16 = const()[name = string("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor<fp16, [49408, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))]; |
| int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)]; |
| tensor<int32, [1, 77]> cast_1 = cast(dtype = cast_1_dtype_0, x = input_ids)[name = string("cast_56")]; |
| tensor<bool, [1, 77]> greater_equal_0 = greater_equal(x = cast_1, y = greater_equal_0_y_0)[name = string("greater_equal_0")]; |
| int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(49408)]; |
| tensor<int32, [1, 77]> add_12 = add(x = cast_1, y = slice_by_index_0)[name = string("add_12")]; |
| tensor<int32, [1, 77]> select_0 = select(a = cast_1, b = add_12, cond = greater_equal_0)[name = string("select_0")]; |
| int32 inputs_embeds_cast_fp16_axis_0 = const()[name = string("inputs_embeds_cast_fp16_axis_0"), val = int32(0)]; |
| tensor<fp16, [1, 77, 768]> inputs_embeds_cast_fp16 = gather(axis = inputs_embeds_cast_fp16_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = select_0, validate_indices = inputs_embeds_validate_indices_0, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16)[name = string("inputs_embeds_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> position_embeddings_to_fp16 = const()[name = string("position_embeddings_to_fp16"), val = tensor<fp16, [1, 77, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(75890816)))]; |
| tensor<fp16, [1, 77, 768]> input_3_cast_fp16 = add(x = inputs_embeds_cast_fp16, y = position_embeddings_to_fp16)[name = string("input_3_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_1_axes_0 = const()[name = string("hidden_states_1_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(76009152)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(76010752)))]; |
| fp16 var_15_to_fp16 = const()[name = string("op_15_to_fp16"), val = fp16(0x1.5p-17)]; |
| tensor<fp16, [1, 77, 768]> hidden_states_1_cast_fp16 = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_3_cast_fp16)[name = string("hidden_states_1_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(76012352)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77192064)))]; |
| tensor<fp16, [1, 77, 768]> linear_0_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16, x = hidden_states_1_cast_fp16)[name = string("linear_0_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(77193664)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78373376)))]; |
| tensor<fp16, [1, 77, 768]> linear_1_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16, x = hidden_states_1_cast_fp16)[name = string("linear_1_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78374976)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(79554688)))]; |
| tensor<fp16, [1, 77, 768]> linear_2_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16, x = hidden_states_1_cast_fp16)[name = string("linear_2_cast_fp16")]; |
| tensor<int32, [4]> var_113 = const()[name = string("op_113"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_114_cast_fp16 = reshape(shape = var_113, x = linear_0_cast_fp16)[name = string("op_114_cast_fp16")]; |
| tensor<int32, [4]> var_116 = const()[name = string("op_116"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_117_cast_fp16 = reshape(shape = var_116, x = linear_1_cast_fp16)[name = string("op_117_cast_fp16")]; |
| tensor<int32, [4]> var_119 = const()[name = string("op_119"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_120_cast_fp16 = reshape(shape = var_119, x = linear_2_cast_fp16)[name = string("op_120_cast_fp16")]; |
| tensor<int32, [4]> value_states_3_perm_0 = const()[name = string("value_states_3_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| fp16 var_17_to_fp16 = const()[name = string("op_17_to_fp16"), val = fp16(0x1p-3)]; |
| tensor<fp16, [1, 77, 12, 64]> mul_0_cast_fp16 = mul(x = var_114_cast_fp16, y = var_17_to_fp16)[name = string("mul_0_cast_fp16")]; |
| bool matmul_0_transpose_y_0 = const()[name = string("matmul_0_transpose_y_0"), val = bool(true)]; |
| bool matmul_0_transpose_x_0 = const()[name = string("matmul_0_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_49_perm_0 = const()[name = string("transpose_49_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_50_perm_0 = const()[name = string("transpose_50_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_50 = transpose(perm = transpose_50_perm_0, x = var_117_cast_fp16)[name = string("transpose_118")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_49 = transpose(perm = transpose_49_perm_0, x = mul_0_cast_fp16)[name = string("transpose_119")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_0_cast_fp16 = matmul(transpose_x = matmul_0_transpose_x_0, transpose_y = matmul_0_transpose_y_0, x = transpose_49, y = transpose_50)[name = string("matmul_0_cast_fp16")]; |
| tensor<fp16, [1, 1, 77, 77]> var_57_to_fp16 = const()[name = string("op_57_to_fp16"), val = tensor<fp16, [1, 1, 77, 77]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(79556288)))]; |
| tensor<fp16, [1, 12, 77, 77]> add_0_cast_fp16 = add(x = matmul_0_cast_fp16, y = var_57_to_fp16)[name = string("add_0_cast_fp16")]; |
| int32 softmax_0_axis_0 = const()[name = string("softmax_0_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_0_cast_fp16 = softmax(axis = softmax_0_axis_0, x = add_0_cast_fp16)[name = string("softmax_0_cast_fp16")]; |
| bool attn_output_1_transpose_x_0 = const()[name = string("attn_output_1_transpose_x_0"), val = bool(false)]; |
| bool attn_output_1_transpose_y_0 = const()[name = string("attn_output_1_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_3_cast_fp16 = transpose(perm = value_states_3_perm_0, x = var_120_cast_fp16)[name = string("transpose_120")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_1_cast_fp16 = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = softmax_0_cast_fp16, y = value_states_3_cast_fp16)[name = string("attn_output_1_cast_fp16")]; |
| tensor<int32, [4]> attn_output_3_perm_0 = const()[name = string("attn_output_3_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_124 = const()[name = string("op_124"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_3_cast_fp16 = transpose(perm = attn_output_3_perm_0, x = attn_output_1_cast_fp16)[name = string("transpose_117")]; |
| tensor<fp16, [1, 77, 768]> input_5_cast_fp16 = reshape(shape = var_124, x = attn_output_3_cast_fp16)[name = string("input_5_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(79568256)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80747968)))]; |
| tensor<fp16, [1, 77, 768]> linear_3_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16, x = input_5_cast_fp16)[name = string("linear_3_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_7_cast_fp16 = add(x = input_3_cast_fp16, y = linear_3_cast_fp16)[name = string("input_7_cast_fp16")]; |
| tensor<int32, [1]> input_9_axes_0 = const()[name = string("input_9_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80749568)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80751168)))]; |
| tensor<fp16, [1, 77, 768]> input_9_cast_fp16 = layer_norm(axes = input_9_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_9_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80752768)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85471424)))]; |
| tensor<fp16, [1, 77, 3072]> linear_4_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16, x = input_9_cast_fp16)[name = string("linear_4_cast_fp16")]; |
| fp16 var_139_to_fp16 = const()[name = string("op_139_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_140_cast_fp16 = mul(x = linear_4_cast_fp16, y = var_139_to_fp16)[name = string("op_140_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_141_cast_fp16 = sigmoid(x = var_140_cast_fp16)[name = string("op_141_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_13_cast_fp16 = mul(x = linear_4_cast_fp16, y = var_141_cast_fp16)[name = string("input_13_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85477632)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(90196288)))]; |
| tensor<fp16, [1, 77, 768]> linear_5_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16, x = input_13_cast_fp16)[name = string("linear_5_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_15_cast_fp16 = add(x = input_7_cast_fp16, y = linear_5_cast_fp16)[name = string("input_15_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_7_axes_0 = const()[name = string("hidden_states_7_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(90197888)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(90199488)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_7_cast_fp16 = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_15_cast_fp16)[name = string("hidden_states_7_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(90201088)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(91380800)))]; |
| tensor<fp16, [1, 77, 768]> linear_6_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16, x = hidden_states_7_cast_fp16)[name = string("linear_6_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(91382400)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(92562112)))]; |
| tensor<fp16, [1, 77, 768]> linear_7_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16, x = hidden_states_7_cast_fp16)[name = string("linear_7_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(92563712)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(93743424)))]; |
| tensor<fp16, [1, 77, 768]> linear_8_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16, x = hidden_states_7_cast_fp16)[name = string("linear_8_cast_fp16")]; |
| tensor<int32, [4]> var_171 = const()[name = string("op_171"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_172_cast_fp16 = reshape(shape = var_171, x = linear_6_cast_fp16)[name = string("op_172_cast_fp16")]; |
| tensor<int32, [4]> var_174 = const()[name = string("op_174"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_175_cast_fp16 = reshape(shape = var_174, x = linear_7_cast_fp16)[name = string("op_175_cast_fp16")]; |
| tensor<int32, [4]> var_177 = const()[name = string("op_177"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_178_cast_fp16 = reshape(shape = var_177, x = linear_8_cast_fp16)[name = string("op_178_cast_fp16")]; |
| tensor<int32, [4]> value_states_7_perm_0 = const()[name = string("value_states_7_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_1_cast_fp16 = mul(x = var_172_cast_fp16, y = var_17_to_fp16)[name = string("mul_1_cast_fp16")]; |
| bool matmul_1_transpose_y_0 = const()[name = string("matmul_1_transpose_y_0"), val = bool(true)]; |
| bool matmul_1_transpose_x_0 = const()[name = string("matmul_1_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_51_perm_0 = const()[name = string("transpose_51_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_52_perm_0 = const()[name = string("transpose_52_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_52 = transpose(perm = transpose_52_perm_0, x = var_175_cast_fp16)[name = string("transpose_114")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_51 = transpose(perm = transpose_51_perm_0, x = mul_1_cast_fp16)[name = string("transpose_115")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_1_cast_fp16 = matmul(transpose_x = matmul_1_transpose_x_0, transpose_y = matmul_1_transpose_y_0, x = transpose_51, y = transpose_52)[name = string("matmul_1_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_1_cast_fp16 = add(x = matmul_1_cast_fp16, y = var_57_to_fp16)[name = string("add_1_cast_fp16")]; |
| int32 softmax_1_axis_0 = const()[name = string("softmax_1_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_1_cast_fp16 = softmax(axis = softmax_1_axis_0, x = add_1_cast_fp16)[name = string("softmax_1_cast_fp16")]; |
| bool attn_output_5_transpose_x_0 = const()[name = string("attn_output_5_transpose_x_0"), val = bool(false)]; |
| bool attn_output_5_transpose_y_0 = const()[name = string("attn_output_5_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_7_cast_fp16 = transpose(perm = value_states_7_perm_0, x = var_178_cast_fp16)[name = string("transpose_116")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_5_cast_fp16 = matmul(transpose_x = attn_output_5_transpose_x_0, transpose_y = attn_output_5_transpose_y_0, x = softmax_1_cast_fp16, y = value_states_7_cast_fp16)[name = string("attn_output_5_cast_fp16")]; |
| tensor<int32, [4]> attn_output_7_perm_0 = const()[name = string("attn_output_7_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_182 = const()[name = string("op_182"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_7_cast_fp16 = transpose(perm = attn_output_7_perm_0, x = attn_output_5_cast_fp16)[name = string("transpose_113")]; |
| tensor<fp16, [1, 77, 768]> input_17_cast_fp16 = reshape(shape = var_182, x = attn_output_7_cast_fp16)[name = string("input_17_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(93745024)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94924736)))]; |
| tensor<fp16, [1, 77, 768]> linear_9_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16, x = input_17_cast_fp16)[name = string("linear_9_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_19_cast_fp16 = add(x = input_15_cast_fp16, y = linear_9_cast_fp16)[name = string("input_19_cast_fp16")]; |
| tensor<int32, [1]> input_21_axes_0 = const()[name = string("input_21_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94926336)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94927936)))]; |
| tensor<fp16, [1, 77, 768]> input_21_cast_fp16 = layer_norm(axes = input_21_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_19_cast_fp16)[name = string("input_21_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94929536)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(99648192)))]; |
| tensor<fp16, [1, 77, 3072]> linear_10_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16, x = input_21_cast_fp16)[name = string("linear_10_cast_fp16")]; |
| fp16 var_197_to_fp16 = const()[name = string("op_197_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_198_cast_fp16 = mul(x = linear_10_cast_fp16, y = var_197_to_fp16)[name = string("op_198_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_199_cast_fp16 = sigmoid(x = var_198_cast_fp16)[name = string("op_199_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_25_cast_fp16 = mul(x = linear_10_cast_fp16, y = var_199_cast_fp16)[name = string("input_25_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(99654400)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(104373056)))]; |
| tensor<fp16, [1, 77, 768]> linear_11_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16, x = input_25_cast_fp16)[name = string("linear_11_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_27_cast_fp16 = add(x = input_19_cast_fp16, y = linear_11_cast_fp16)[name = string("input_27_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_13_axes_0 = const()[name = string("hidden_states_13_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(104374656)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(104376256)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_13_cast_fp16 = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_27_cast_fp16)[name = string("hidden_states_13_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(104377856)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(105557568)))]; |
| tensor<fp16, [1, 77, 768]> linear_12_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16, x = hidden_states_13_cast_fp16)[name = string("linear_12_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(105559168)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(106738880)))]; |
| tensor<fp16, [1, 77, 768]> linear_13_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16, x = hidden_states_13_cast_fp16)[name = string("linear_13_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(106740480)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(107920192)))]; |
| tensor<fp16, [1, 77, 768]> linear_14_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16, x = hidden_states_13_cast_fp16)[name = string("linear_14_cast_fp16")]; |
| tensor<int32, [4]> var_229 = const()[name = string("op_229"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_230_cast_fp16 = reshape(shape = var_229, x = linear_12_cast_fp16)[name = string("op_230_cast_fp16")]; |
| tensor<int32, [4]> var_232 = const()[name = string("op_232"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_233_cast_fp16 = reshape(shape = var_232, x = linear_13_cast_fp16)[name = string("op_233_cast_fp16")]; |
| tensor<int32, [4]> var_235 = const()[name = string("op_235"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_236_cast_fp16 = reshape(shape = var_235, x = linear_14_cast_fp16)[name = string("op_236_cast_fp16")]; |
| tensor<int32, [4]> value_states_11_perm_0 = const()[name = string("value_states_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_2_cast_fp16 = mul(x = var_230_cast_fp16, y = var_17_to_fp16)[name = string("mul_2_cast_fp16")]; |
| bool matmul_2_transpose_y_0 = const()[name = string("matmul_2_transpose_y_0"), val = bool(true)]; |
| bool matmul_2_transpose_x_0 = const()[name = string("matmul_2_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_53_perm_0 = const()[name = string("transpose_53_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_54_perm_0 = const()[name = string("transpose_54_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_54 = transpose(perm = transpose_54_perm_0, x = var_233_cast_fp16)[name = string("transpose_110")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_53 = transpose(perm = transpose_53_perm_0, x = mul_2_cast_fp16)[name = string("transpose_111")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_2_cast_fp16 = matmul(transpose_x = matmul_2_transpose_x_0, transpose_y = matmul_2_transpose_y_0, x = transpose_53, y = transpose_54)[name = string("matmul_2_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_2_cast_fp16 = add(x = matmul_2_cast_fp16, y = var_57_to_fp16)[name = string("add_2_cast_fp16")]; |
| int32 softmax_2_axis_0 = const()[name = string("softmax_2_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_2_cast_fp16 = softmax(axis = softmax_2_axis_0, x = add_2_cast_fp16)[name = string("softmax_2_cast_fp16")]; |
| bool attn_output_9_transpose_x_0 = const()[name = string("attn_output_9_transpose_x_0"), val = bool(false)]; |
| bool attn_output_9_transpose_y_0 = const()[name = string("attn_output_9_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_11_cast_fp16 = transpose(perm = value_states_11_perm_0, x = var_236_cast_fp16)[name = string("transpose_112")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_9_cast_fp16 = matmul(transpose_x = attn_output_9_transpose_x_0, transpose_y = attn_output_9_transpose_y_0, x = softmax_2_cast_fp16, y = value_states_11_cast_fp16)[name = string("attn_output_9_cast_fp16")]; |
| tensor<int32, [4]> attn_output_11_perm_0 = const()[name = string("attn_output_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_240 = const()[name = string("op_240"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_11_cast_fp16 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast_fp16)[name = string("transpose_109")]; |
| tensor<fp16, [1, 77, 768]> input_29_cast_fp16 = reshape(shape = var_240, x = attn_output_11_cast_fp16)[name = string("input_29_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(107921792)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(109101504)))]; |
| tensor<fp16, [1, 77, 768]> linear_15_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16, x = input_29_cast_fp16)[name = string("linear_15_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_31_cast_fp16 = add(x = input_27_cast_fp16, y = linear_15_cast_fp16)[name = string("input_31_cast_fp16")]; |
| tensor<int32, [1]> input_33_axes_0 = const()[name = string("input_33_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(109103104)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(109104704)))]; |
| tensor<fp16, [1, 77, 768]> input_33_cast_fp16 = layer_norm(axes = input_33_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(109106304)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(113824960)))]; |
| tensor<fp16, [1, 77, 3072]> linear_16_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16, x = input_33_cast_fp16)[name = string("linear_16_cast_fp16")]; |
| fp16 var_255_to_fp16 = const()[name = string("op_255_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_256_cast_fp16 = mul(x = linear_16_cast_fp16, y = var_255_to_fp16)[name = string("op_256_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_257_cast_fp16 = sigmoid(x = var_256_cast_fp16)[name = string("op_257_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_37_cast_fp16 = mul(x = linear_16_cast_fp16, y = var_257_cast_fp16)[name = string("input_37_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(113831168)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(118549824)))]; |
| tensor<fp16, [1, 77, 768]> linear_17_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16, x = input_37_cast_fp16)[name = string("linear_17_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_39_cast_fp16 = add(x = input_31_cast_fp16, y = linear_17_cast_fp16)[name = string("input_39_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_19_axes_0 = const()[name = string("hidden_states_19_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(118551424)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(118553024)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_19_cast_fp16 = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_39_cast_fp16)[name = string("hidden_states_19_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(118554624)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(119734336)))]; |
| tensor<fp16, [1, 77, 768]> linear_18_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16, x = hidden_states_19_cast_fp16)[name = string("linear_18_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(119735936)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120915648)))]; |
| tensor<fp16, [1, 77, 768]> linear_19_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16, x = hidden_states_19_cast_fp16)[name = string("linear_19_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120917248)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(122096960)))]; |
| tensor<fp16, [1, 77, 768]> linear_20_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16, x = hidden_states_19_cast_fp16)[name = string("linear_20_cast_fp16")]; |
| tensor<int32, [4]> var_287 = const()[name = string("op_287"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_288_cast_fp16 = reshape(shape = var_287, x = linear_18_cast_fp16)[name = string("op_288_cast_fp16")]; |
| tensor<int32, [4]> var_290 = const()[name = string("op_290"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_291_cast_fp16 = reshape(shape = var_290, x = linear_19_cast_fp16)[name = string("op_291_cast_fp16")]; |
| tensor<int32, [4]> var_293 = const()[name = string("op_293"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_294_cast_fp16 = reshape(shape = var_293, x = linear_20_cast_fp16)[name = string("op_294_cast_fp16")]; |
| tensor<int32, [4]> value_states_15_perm_0 = const()[name = string("value_states_15_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_3_cast_fp16 = mul(x = var_288_cast_fp16, y = var_17_to_fp16)[name = string("mul_3_cast_fp16")]; |
| bool matmul_3_transpose_y_0 = const()[name = string("matmul_3_transpose_y_0"), val = bool(true)]; |
| bool matmul_3_transpose_x_0 = const()[name = string("matmul_3_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_55_perm_0 = const()[name = string("transpose_55_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_56_perm_0 = const()[name = string("transpose_56_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_56 = transpose(perm = transpose_56_perm_0, x = var_291_cast_fp16)[name = string("transpose_106")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_55 = transpose(perm = transpose_55_perm_0, x = mul_3_cast_fp16)[name = string("transpose_107")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_3_cast_fp16 = matmul(transpose_x = matmul_3_transpose_x_0, transpose_y = matmul_3_transpose_y_0, x = transpose_55, y = transpose_56)[name = string("matmul_3_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_3_cast_fp16 = add(x = matmul_3_cast_fp16, y = var_57_to_fp16)[name = string("add_3_cast_fp16")]; |
| int32 softmax_3_axis_0 = const()[name = string("softmax_3_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_3_cast_fp16 = softmax(axis = softmax_3_axis_0, x = add_3_cast_fp16)[name = string("softmax_3_cast_fp16")]; |
| bool attn_output_13_transpose_x_0 = const()[name = string("attn_output_13_transpose_x_0"), val = bool(false)]; |
| bool attn_output_13_transpose_y_0 = const()[name = string("attn_output_13_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_15_cast_fp16 = transpose(perm = value_states_15_perm_0, x = var_294_cast_fp16)[name = string("transpose_108")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_13_cast_fp16 = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = softmax_3_cast_fp16, y = value_states_15_cast_fp16)[name = string("attn_output_13_cast_fp16")]; |
| tensor<int32, [4]> attn_output_15_perm_0 = const()[name = string("attn_output_15_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_298 = const()[name = string("op_298"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_15_cast_fp16 = transpose(perm = attn_output_15_perm_0, x = attn_output_13_cast_fp16)[name = string("transpose_105")]; |
| tensor<fp16, [1, 77, 768]> input_41_cast_fp16 = reshape(shape = var_298, x = attn_output_15_cast_fp16)[name = string("input_41_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(122098560)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123278272)))]; |
| tensor<fp16, [1, 77, 768]> linear_21_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16, x = input_41_cast_fp16)[name = string("linear_21_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_43_cast_fp16 = add(x = input_39_cast_fp16, y = linear_21_cast_fp16)[name = string("input_43_cast_fp16")]; |
| tensor<int32, [1]> input_45_axes_0 = const()[name = string("input_45_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123279872)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123281472)))]; |
| tensor<fp16, [1, 77, 768]> input_45_cast_fp16 = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_43_cast_fp16)[name = string("input_45_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(123283072)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(128001728)))]; |
| tensor<fp16, [1, 77, 3072]> linear_22_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16, x = input_45_cast_fp16)[name = string("linear_22_cast_fp16")]; |
| fp16 var_313_to_fp16 = const()[name = string("op_313_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_314_cast_fp16 = mul(x = linear_22_cast_fp16, y = var_313_to_fp16)[name = string("op_314_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_315_cast_fp16 = sigmoid(x = var_314_cast_fp16)[name = string("op_315_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_49_cast_fp16 = mul(x = linear_22_cast_fp16, y = var_315_cast_fp16)[name = string("input_49_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(128007936)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(132726592)))]; |
| tensor<fp16, [1, 77, 768]> linear_23_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16, x = input_49_cast_fp16)[name = string("linear_23_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_51_cast_fp16 = add(x = input_43_cast_fp16, y = linear_23_cast_fp16)[name = string("input_51_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_25_axes_0 = const()[name = string("hidden_states_25_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(132728192)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(132729792)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_25_cast_fp16 = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_51_cast_fp16)[name = string("hidden_states_25_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(132731392)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(133911104)))]; |
| tensor<fp16, [1, 77, 768]> linear_24_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16, x = hidden_states_25_cast_fp16)[name = string("linear_24_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(133912704)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(135092416)))]; |
| tensor<fp16, [1, 77, 768]> linear_25_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16, x = hidden_states_25_cast_fp16)[name = string("linear_25_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(135094016)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(136273728)))]; |
| tensor<fp16, [1, 77, 768]> linear_26_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16, x = hidden_states_25_cast_fp16)[name = string("linear_26_cast_fp16")]; |
| tensor<int32, [4]> var_345 = const()[name = string("op_345"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_346_cast_fp16 = reshape(shape = var_345, x = linear_24_cast_fp16)[name = string("op_346_cast_fp16")]; |
| tensor<int32, [4]> var_348 = const()[name = string("op_348"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_349_cast_fp16 = reshape(shape = var_348, x = linear_25_cast_fp16)[name = string("op_349_cast_fp16")]; |
| tensor<int32, [4]> var_351 = const()[name = string("op_351"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_352_cast_fp16 = reshape(shape = var_351, x = linear_26_cast_fp16)[name = string("op_352_cast_fp16")]; |
| tensor<int32, [4]> value_states_19_perm_0 = const()[name = string("value_states_19_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_4_cast_fp16 = mul(x = var_346_cast_fp16, y = var_17_to_fp16)[name = string("mul_4_cast_fp16")]; |
| bool matmul_4_transpose_y_0 = const()[name = string("matmul_4_transpose_y_0"), val = bool(true)]; |
| bool matmul_4_transpose_x_0 = const()[name = string("matmul_4_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_57_perm_0 = const()[name = string("transpose_57_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_58_perm_0 = const()[name = string("transpose_58_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_58 = transpose(perm = transpose_58_perm_0, x = var_349_cast_fp16)[name = string("transpose_102")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_57 = transpose(perm = transpose_57_perm_0, x = mul_4_cast_fp16)[name = string("transpose_103")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_4_cast_fp16 = matmul(transpose_x = matmul_4_transpose_x_0, transpose_y = matmul_4_transpose_y_0, x = transpose_57, y = transpose_58)[name = string("matmul_4_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_4_cast_fp16 = add(x = matmul_4_cast_fp16, y = var_57_to_fp16)[name = string("add_4_cast_fp16")]; |
| int32 softmax_4_axis_0 = const()[name = string("softmax_4_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_4_cast_fp16 = softmax(axis = softmax_4_axis_0, x = add_4_cast_fp16)[name = string("softmax_4_cast_fp16")]; |
| bool attn_output_17_transpose_x_0 = const()[name = string("attn_output_17_transpose_x_0"), val = bool(false)]; |
| bool attn_output_17_transpose_y_0 = const()[name = string("attn_output_17_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_19_cast_fp16 = transpose(perm = value_states_19_perm_0, x = var_352_cast_fp16)[name = string("transpose_104")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_17_cast_fp16 = matmul(transpose_x = attn_output_17_transpose_x_0, transpose_y = attn_output_17_transpose_y_0, x = softmax_4_cast_fp16, y = value_states_19_cast_fp16)[name = string("attn_output_17_cast_fp16")]; |
| tensor<int32, [4]> attn_output_19_perm_0 = const()[name = string("attn_output_19_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_356 = const()[name = string("op_356"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_19_cast_fp16 = transpose(perm = attn_output_19_perm_0, x = attn_output_17_cast_fp16)[name = string("transpose_101")]; |
| tensor<fp16, [1, 77, 768]> input_53_cast_fp16 = reshape(shape = var_356, x = attn_output_19_cast_fp16)[name = string("input_53_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(136275328)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137455040)))]; |
| tensor<fp16, [1, 77, 768]> linear_27_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16, x = input_53_cast_fp16)[name = string("linear_27_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_55_cast_fp16 = add(x = input_51_cast_fp16, y = linear_27_cast_fp16)[name = string("input_55_cast_fp16")]; |
| tensor<int32, [1]> input_57_axes_0 = const()[name = string("input_57_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137456640)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137458240)))]; |
| tensor<fp16, [1, 77, 768]> input_57_cast_fp16 = layer_norm(axes = input_57_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_57_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(137459840)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142178496)))]; |
| tensor<fp16, [1, 77, 3072]> linear_28_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16, x = input_57_cast_fp16)[name = string("linear_28_cast_fp16")]; |
| fp16 var_371_to_fp16 = const()[name = string("op_371_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_372_cast_fp16 = mul(x = linear_28_cast_fp16, y = var_371_to_fp16)[name = string("op_372_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_373_cast_fp16 = sigmoid(x = var_372_cast_fp16)[name = string("op_373_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_61_cast_fp16 = mul(x = linear_28_cast_fp16, y = var_373_cast_fp16)[name = string("input_61_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142184704)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(146903360)))]; |
| tensor<fp16, [1, 77, 768]> linear_29_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16, x = input_61_cast_fp16)[name = string("linear_29_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_63_cast_fp16 = add(x = input_55_cast_fp16, y = linear_29_cast_fp16)[name = string("input_63_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_31_axes_0 = const()[name = string("hidden_states_31_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(146904960)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(146906560)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_31_cast_fp16 = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_63_cast_fp16)[name = string("hidden_states_31_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(146908160)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(148087872)))]; |
| tensor<fp16, [1, 77, 768]> linear_30_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16, x = hidden_states_31_cast_fp16)[name = string("linear_30_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(148089472)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(149269184)))]; |
| tensor<fp16, [1, 77, 768]> linear_31_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16, x = hidden_states_31_cast_fp16)[name = string("linear_31_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(149270784)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(150450496)))]; |
| tensor<fp16, [1, 77, 768]> linear_32_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16, x = hidden_states_31_cast_fp16)[name = string("linear_32_cast_fp16")]; |
| tensor<int32, [4]> var_403 = const()[name = string("op_403"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_404_cast_fp16 = reshape(shape = var_403, x = linear_30_cast_fp16)[name = string("op_404_cast_fp16")]; |
| tensor<int32, [4]> var_406 = const()[name = string("op_406"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_407_cast_fp16 = reshape(shape = var_406, x = linear_31_cast_fp16)[name = string("op_407_cast_fp16")]; |
| tensor<int32, [4]> var_409 = const()[name = string("op_409"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_410_cast_fp16 = reshape(shape = var_409, x = linear_32_cast_fp16)[name = string("op_410_cast_fp16")]; |
| tensor<int32, [4]> value_states_23_perm_0 = const()[name = string("value_states_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_5_cast_fp16 = mul(x = var_404_cast_fp16, y = var_17_to_fp16)[name = string("mul_5_cast_fp16")]; |
| bool matmul_5_transpose_y_0 = const()[name = string("matmul_5_transpose_y_0"), val = bool(true)]; |
| bool matmul_5_transpose_x_0 = const()[name = string("matmul_5_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_59_perm_0 = const()[name = string("transpose_59_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_60_perm_0 = const()[name = string("transpose_60_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_60 = transpose(perm = transpose_60_perm_0, x = var_407_cast_fp16)[name = string("transpose_98")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_59 = transpose(perm = transpose_59_perm_0, x = mul_5_cast_fp16)[name = string("transpose_99")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_5_cast_fp16 = matmul(transpose_x = matmul_5_transpose_x_0, transpose_y = matmul_5_transpose_y_0, x = transpose_59, y = transpose_60)[name = string("matmul_5_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_5_cast_fp16 = add(x = matmul_5_cast_fp16, y = var_57_to_fp16)[name = string("add_5_cast_fp16")]; |
| int32 softmax_5_axis_0 = const()[name = string("softmax_5_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_5_cast_fp16 = softmax(axis = softmax_5_axis_0, x = add_5_cast_fp16)[name = string("softmax_5_cast_fp16")]; |
| bool attn_output_21_transpose_x_0 = const()[name = string("attn_output_21_transpose_x_0"), val = bool(false)]; |
| bool attn_output_21_transpose_y_0 = const()[name = string("attn_output_21_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_23_cast_fp16 = transpose(perm = value_states_23_perm_0, x = var_410_cast_fp16)[name = string("transpose_100")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_21_cast_fp16 = matmul(transpose_x = attn_output_21_transpose_x_0, transpose_y = attn_output_21_transpose_y_0, x = softmax_5_cast_fp16, y = value_states_23_cast_fp16)[name = string("attn_output_21_cast_fp16")]; |
| tensor<int32, [4]> attn_output_23_perm_0 = const()[name = string("attn_output_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_414 = const()[name = string("op_414"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_23_cast_fp16 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast_fp16)[name = string("transpose_97")]; |
| tensor<fp16, [1, 77, 768]> input_65_cast_fp16 = reshape(shape = var_414, x = attn_output_23_cast_fp16)[name = string("input_65_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(150452096)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(151631808)))]; |
| tensor<fp16, [1, 77, 768]> linear_33_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16, x = input_65_cast_fp16)[name = string("linear_33_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_67_cast_fp16 = add(x = input_63_cast_fp16, y = linear_33_cast_fp16)[name = string("input_67_cast_fp16")]; |
| tensor<int32, [1]> input_69_axes_0 = const()[name = string("input_69_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(151633408)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(151635008)))]; |
| tensor<fp16, [1, 77, 768]> input_69_cast_fp16 = layer_norm(axes = input_69_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_67_cast_fp16)[name = string("input_69_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(151636608)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(156355264)))]; |
| tensor<fp16, [1, 77, 3072]> linear_34_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16, x = input_69_cast_fp16)[name = string("linear_34_cast_fp16")]; |
| fp16 var_429_to_fp16 = const()[name = string("op_429_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_430_cast_fp16 = mul(x = linear_34_cast_fp16, y = var_429_to_fp16)[name = string("op_430_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_431_cast_fp16 = sigmoid(x = var_430_cast_fp16)[name = string("op_431_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_73_cast_fp16 = mul(x = linear_34_cast_fp16, y = var_431_cast_fp16)[name = string("input_73_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(156361472)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(161080128)))]; |
| tensor<fp16, [1, 77, 768]> linear_35_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16, x = input_73_cast_fp16)[name = string("linear_35_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_75_cast_fp16 = add(x = input_67_cast_fp16, y = linear_35_cast_fp16)[name = string("input_75_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_37_axes_0 = const()[name = string("hidden_states_37_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(161081728)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(161083328)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_37_cast_fp16 = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_75_cast_fp16)[name = string("hidden_states_37_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(161084928)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(162264640)))]; |
| tensor<fp16, [1, 77, 768]> linear_36_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16, x = hidden_states_37_cast_fp16)[name = string("linear_36_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(162266240)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(163445952)))]; |
| tensor<fp16, [1, 77, 768]> linear_37_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16, x = hidden_states_37_cast_fp16)[name = string("linear_37_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(163447552)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(164627264)))]; |
| tensor<fp16, [1, 77, 768]> linear_38_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16, x = hidden_states_37_cast_fp16)[name = string("linear_38_cast_fp16")]; |
| tensor<int32, [4]> var_461 = const()[name = string("op_461"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_462_cast_fp16 = reshape(shape = var_461, x = linear_36_cast_fp16)[name = string("op_462_cast_fp16")]; |
| tensor<int32, [4]> var_464 = const()[name = string("op_464"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_465_cast_fp16 = reshape(shape = var_464, x = linear_37_cast_fp16)[name = string("op_465_cast_fp16")]; |
| tensor<int32, [4]> var_467 = const()[name = string("op_467"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_468_cast_fp16 = reshape(shape = var_467, x = linear_38_cast_fp16)[name = string("op_468_cast_fp16")]; |
| tensor<int32, [4]> value_states_27_perm_0 = const()[name = string("value_states_27_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_6_cast_fp16 = mul(x = var_462_cast_fp16, y = var_17_to_fp16)[name = string("mul_6_cast_fp16")]; |
| bool matmul_6_transpose_y_0 = const()[name = string("matmul_6_transpose_y_0"), val = bool(true)]; |
| bool matmul_6_transpose_x_0 = const()[name = string("matmul_6_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_61_perm_0 = const()[name = string("transpose_61_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_62_perm_0 = const()[name = string("transpose_62_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_62 = transpose(perm = transpose_62_perm_0, x = var_465_cast_fp16)[name = string("transpose_94")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_61 = transpose(perm = transpose_61_perm_0, x = mul_6_cast_fp16)[name = string("transpose_95")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_6_cast_fp16 = matmul(transpose_x = matmul_6_transpose_x_0, transpose_y = matmul_6_transpose_y_0, x = transpose_61, y = transpose_62)[name = string("matmul_6_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_6_cast_fp16 = add(x = matmul_6_cast_fp16, y = var_57_to_fp16)[name = string("add_6_cast_fp16")]; |
| int32 softmax_6_axis_0 = const()[name = string("softmax_6_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_6_cast_fp16 = softmax(axis = softmax_6_axis_0, x = add_6_cast_fp16)[name = string("softmax_6_cast_fp16")]; |
| bool attn_output_25_transpose_x_0 = const()[name = string("attn_output_25_transpose_x_0"), val = bool(false)]; |
| bool attn_output_25_transpose_y_0 = const()[name = string("attn_output_25_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_27_cast_fp16 = transpose(perm = value_states_27_perm_0, x = var_468_cast_fp16)[name = string("transpose_96")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_25_cast_fp16 = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = softmax_6_cast_fp16, y = value_states_27_cast_fp16)[name = string("attn_output_25_cast_fp16")]; |
| tensor<int32, [4]> attn_output_27_perm_0 = const()[name = string("attn_output_27_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_472 = const()[name = string("op_472"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_27_cast_fp16 = transpose(perm = attn_output_27_perm_0, x = attn_output_25_cast_fp16)[name = string("transpose_93")]; |
| tensor<fp16, [1, 77, 768]> input_77_cast_fp16 = reshape(shape = var_472, x = attn_output_27_cast_fp16)[name = string("input_77_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(164628864)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(165808576)))]; |
| tensor<fp16, [1, 77, 768]> linear_39_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16, x = input_77_cast_fp16)[name = string("linear_39_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_79_cast_fp16 = add(x = input_75_cast_fp16, y = linear_39_cast_fp16)[name = string("input_79_cast_fp16")]; |
| tensor<int32, [1]> input_81_axes_0 = const()[name = string("input_81_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(165810176)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(165811776)))]; |
| tensor<fp16, [1, 77, 768]> input_81_cast_fp16 = layer_norm(axes = input_81_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_81_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(165813376)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(170532032)))]; |
| tensor<fp16, [1, 77, 3072]> linear_40_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16, x = input_81_cast_fp16)[name = string("linear_40_cast_fp16")]; |
| fp16 var_487_to_fp16 = const()[name = string("op_487_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_488_cast_fp16 = mul(x = linear_40_cast_fp16, y = var_487_to_fp16)[name = string("op_488_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_489_cast_fp16 = sigmoid(x = var_488_cast_fp16)[name = string("op_489_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_85_cast_fp16 = mul(x = linear_40_cast_fp16, y = var_489_cast_fp16)[name = string("input_85_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(170538240)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(175256896)))]; |
| tensor<fp16, [1, 77, 768]> linear_41_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16, x = input_85_cast_fp16)[name = string("linear_41_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_87_cast_fp16 = add(x = input_79_cast_fp16, y = linear_41_cast_fp16)[name = string("input_87_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_43_axes_0 = const()[name = string("hidden_states_43_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(175258496)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(175260096)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_43_cast_fp16 = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_87_cast_fp16)[name = string("hidden_states_43_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(175261696)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(176441408)))]; |
| tensor<fp16, [1, 77, 768]> linear_42_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16, x = hidden_states_43_cast_fp16)[name = string("linear_42_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(176443008)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(177622720)))]; |
| tensor<fp16, [1, 77, 768]> linear_43_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16, x = hidden_states_43_cast_fp16)[name = string("linear_43_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(177624320)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(178804032)))]; |
| tensor<fp16, [1, 77, 768]> linear_44_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16, x = hidden_states_43_cast_fp16)[name = string("linear_44_cast_fp16")]; |
| tensor<int32, [4]> var_519 = const()[name = string("op_519"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_520_cast_fp16 = reshape(shape = var_519, x = linear_42_cast_fp16)[name = string("op_520_cast_fp16")]; |
| tensor<int32, [4]> var_522 = const()[name = string("op_522"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_523_cast_fp16 = reshape(shape = var_522, x = linear_43_cast_fp16)[name = string("op_523_cast_fp16")]; |
| tensor<int32, [4]> var_525 = const()[name = string("op_525"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_526_cast_fp16 = reshape(shape = var_525, x = linear_44_cast_fp16)[name = string("op_526_cast_fp16")]; |
| tensor<int32, [4]> value_states_31_perm_0 = const()[name = string("value_states_31_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_7_cast_fp16 = mul(x = var_520_cast_fp16, y = var_17_to_fp16)[name = string("mul_7_cast_fp16")]; |
| bool matmul_7_transpose_y_0 = const()[name = string("matmul_7_transpose_y_0"), val = bool(true)]; |
| bool matmul_7_transpose_x_0 = const()[name = string("matmul_7_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_63_perm_0 = const()[name = string("transpose_63_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_64_perm_0 = const()[name = string("transpose_64_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_64 = transpose(perm = transpose_64_perm_0, x = var_523_cast_fp16)[name = string("transpose_90")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_63 = transpose(perm = transpose_63_perm_0, x = mul_7_cast_fp16)[name = string("transpose_91")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_7_cast_fp16 = matmul(transpose_x = matmul_7_transpose_x_0, transpose_y = matmul_7_transpose_y_0, x = transpose_63, y = transpose_64)[name = string("matmul_7_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_7_cast_fp16 = add(x = matmul_7_cast_fp16, y = var_57_to_fp16)[name = string("add_7_cast_fp16")]; |
| int32 softmax_7_axis_0 = const()[name = string("softmax_7_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_7_cast_fp16 = softmax(axis = softmax_7_axis_0, x = add_7_cast_fp16)[name = string("softmax_7_cast_fp16")]; |
| bool attn_output_29_transpose_x_0 = const()[name = string("attn_output_29_transpose_x_0"), val = bool(false)]; |
| bool attn_output_29_transpose_y_0 = const()[name = string("attn_output_29_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_31_cast_fp16 = transpose(perm = value_states_31_perm_0, x = var_526_cast_fp16)[name = string("transpose_92")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_29_cast_fp16 = matmul(transpose_x = attn_output_29_transpose_x_0, transpose_y = attn_output_29_transpose_y_0, x = softmax_7_cast_fp16, y = value_states_31_cast_fp16)[name = string("attn_output_29_cast_fp16")]; |
| tensor<int32, [4]> attn_output_31_perm_0 = const()[name = string("attn_output_31_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_530 = const()[name = string("op_530"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_31_cast_fp16 = transpose(perm = attn_output_31_perm_0, x = attn_output_29_cast_fp16)[name = string("transpose_89")]; |
| tensor<fp16, [1, 77, 768]> input_89_cast_fp16 = reshape(shape = var_530, x = attn_output_31_cast_fp16)[name = string("input_89_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(178805632)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(179985344)))]; |
| tensor<fp16, [1, 77, 768]> linear_45_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16, x = input_89_cast_fp16)[name = string("linear_45_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_91_cast_fp16 = add(x = input_87_cast_fp16, y = linear_45_cast_fp16)[name = string("input_91_cast_fp16")]; |
| tensor<int32, [1]> input_93_axes_0 = const()[name = string("input_93_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(179986944)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(179988544)))]; |
| tensor<fp16, [1, 77, 768]> input_93_cast_fp16 = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_91_cast_fp16)[name = string("input_93_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(179990144)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184708800)))]; |
| tensor<fp16, [1, 77, 3072]> linear_46_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16, x = input_93_cast_fp16)[name = string("linear_46_cast_fp16")]; |
| fp16 var_545_to_fp16 = const()[name = string("op_545_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_546_cast_fp16 = mul(x = linear_46_cast_fp16, y = var_545_to_fp16)[name = string("op_546_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_547_cast_fp16 = sigmoid(x = var_546_cast_fp16)[name = string("op_547_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_97_cast_fp16 = mul(x = linear_46_cast_fp16, y = var_547_cast_fp16)[name = string("input_97_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(184715008)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189433664)))]; |
| tensor<fp16, [1, 77, 768]> linear_47_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16, x = input_97_cast_fp16)[name = string("linear_47_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_99_cast_fp16 = add(x = input_91_cast_fp16, y = linear_47_cast_fp16)[name = string("input_99_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_49_axes_0 = const()[name = string("hidden_states_49_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189435264)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189436864)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_49_cast_fp16 = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_99_cast_fp16)[name = string("hidden_states_49_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(189438464)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(190618176)))]; |
| tensor<fp16, [1, 77, 768]> linear_48_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16, x = hidden_states_49_cast_fp16)[name = string("linear_48_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(190619776)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(191799488)))]; |
| tensor<fp16, [1, 77, 768]> linear_49_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16, x = hidden_states_49_cast_fp16)[name = string("linear_49_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(191801088)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192980800)))]; |
| tensor<fp16, [1, 77, 768]> linear_50_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16, x = hidden_states_49_cast_fp16)[name = string("linear_50_cast_fp16")]; |
| tensor<int32, [4]> var_577 = const()[name = string("op_577"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_578_cast_fp16 = reshape(shape = var_577, x = linear_48_cast_fp16)[name = string("op_578_cast_fp16")]; |
| tensor<int32, [4]> var_580 = const()[name = string("op_580"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_581_cast_fp16 = reshape(shape = var_580, x = linear_49_cast_fp16)[name = string("op_581_cast_fp16")]; |
| tensor<int32, [4]> var_583 = const()[name = string("op_583"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_584_cast_fp16 = reshape(shape = var_583, x = linear_50_cast_fp16)[name = string("op_584_cast_fp16")]; |
| tensor<int32, [4]> value_states_35_perm_0 = const()[name = string("value_states_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_8_cast_fp16 = mul(x = var_578_cast_fp16, y = var_17_to_fp16)[name = string("mul_8_cast_fp16")]; |
| bool matmul_8_transpose_y_0 = const()[name = string("matmul_8_transpose_y_0"), val = bool(true)]; |
| bool matmul_8_transpose_x_0 = const()[name = string("matmul_8_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_65_perm_0 = const()[name = string("transpose_65_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_66_perm_0 = const()[name = string("transpose_66_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_66 = transpose(perm = transpose_66_perm_0, x = var_581_cast_fp16)[name = string("transpose_86")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_65 = transpose(perm = transpose_65_perm_0, x = mul_8_cast_fp16)[name = string("transpose_87")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_8_cast_fp16 = matmul(transpose_x = matmul_8_transpose_x_0, transpose_y = matmul_8_transpose_y_0, x = transpose_65, y = transpose_66)[name = string("matmul_8_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_8_cast_fp16 = add(x = matmul_8_cast_fp16, y = var_57_to_fp16)[name = string("add_8_cast_fp16")]; |
| int32 softmax_8_axis_0 = const()[name = string("softmax_8_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_8_cast_fp16 = softmax(axis = softmax_8_axis_0, x = add_8_cast_fp16)[name = string("softmax_8_cast_fp16")]; |
| bool attn_output_33_transpose_x_0 = const()[name = string("attn_output_33_transpose_x_0"), val = bool(false)]; |
| bool attn_output_33_transpose_y_0 = const()[name = string("attn_output_33_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_35_cast_fp16 = transpose(perm = value_states_35_perm_0, x = var_584_cast_fp16)[name = string("transpose_88")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_33_cast_fp16 = matmul(transpose_x = attn_output_33_transpose_x_0, transpose_y = attn_output_33_transpose_y_0, x = softmax_8_cast_fp16, y = value_states_35_cast_fp16)[name = string("attn_output_33_cast_fp16")]; |
| tensor<int32, [4]> attn_output_35_perm_0 = const()[name = string("attn_output_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_588 = const()[name = string("op_588"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_35_cast_fp16 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast_fp16)[name = string("transpose_85")]; |
| tensor<fp16, [1, 77, 768]> input_101_cast_fp16 = reshape(shape = var_588, x = attn_output_35_cast_fp16)[name = string("input_101_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192982400)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(194162112)))]; |
| tensor<fp16, [1, 77, 768]> linear_51_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16, x = input_101_cast_fp16)[name = string("linear_51_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_103_cast_fp16 = add(x = input_99_cast_fp16, y = linear_51_cast_fp16)[name = string("input_103_cast_fp16")]; |
| tensor<int32, [1]> input_105_axes_0 = const()[name = string("input_105_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(194163712)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(194165312)))]; |
| tensor<fp16, [1, 77, 768]> input_105_cast_fp16 = layer_norm(axes = input_105_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_103_cast_fp16)[name = string("input_105_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(194166912)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(198885568)))]; |
| tensor<fp16, [1, 77, 3072]> linear_52_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16, x = input_105_cast_fp16)[name = string("linear_52_cast_fp16")]; |
| fp16 var_603_to_fp16 = const()[name = string("op_603_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_604_cast_fp16 = mul(x = linear_52_cast_fp16, y = var_603_to_fp16)[name = string("op_604_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_605_cast_fp16 = sigmoid(x = var_604_cast_fp16)[name = string("op_605_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_109_cast_fp16 = mul(x = linear_52_cast_fp16, y = var_605_cast_fp16)[name = string("input_109_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(198891776)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(203610432)))]; |
| tensor<fp16, [1, 77, 768]> linear_53_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16, x = input_109_cast_fp16)[name = string("linear_53_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_111_cast_fp16 = add(x = input_103_cast_fp16, y = linear_53_cast_fp16)[name = string("input_111_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_55_axes_0 = const()[name = string("hidden_states_55_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(203612032)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(203613632)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_55_cast_fp16 = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_111_cast_fp16)[name = string("hidden_states_55_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(203615232)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(204794944)))]; |
| tensor<fp16, [1, 77, 768]> linear_54_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16, x = hidden_states_55_cast_fp16)[name = string("linear_54_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(204796544)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(205976256)))]; |
| tensor<fp16, [1, 77, 768]> linear_55_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16, x = hidden_states_55_cast_fp16)[name = string("linear_55_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(205977856)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(207157568)))]; |
| tensor<fp16, [1, 77, 768]> linear_56_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16, x = hidden_states_55_cast_fp16)[name = string("linear_56_cast_fp16")]; |
| tensor<int32, [4]> var_635 = const()[name = string("op_635"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_636_cast_fp16 = reshape(shape = var_635, x = linear_54_cast_fp16)[name = string("op_636_cast_fp16")]; |
| tensor<int32, [4]> var_638 = const()[name = string("op_638"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_639_cast_fp16 = reshape(shape = var_638, x = linear_55_cast_fp16)[name = string("op_639_cast_fp16")]; |
| tensor<int32, [4]> var_641 = const()[name = string("op_641"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_642_cast_fp16 = reshape(shape = var_641, x = linear_56_cast_fp16)[name = string("op_642_cast_fp16")]; |
| tensor<int32, [4]> value_states_39_perm_0 = const()[name = string("value_states_39_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_9_cast_fp16 = mul(x = var_636_cast_fp16, y = var_17_to_fp16)[name = string("mul_9_cast_fp16")]; |
| bool matmul_9_transpose_y_0 = const()[name = string("matmul_9_transpose_y_0"), val = bool(true)]; |
| bool matmul_9_transpose_x_0 = const()[name = string("matmul_9_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_67_perm_0 = const()[name = string("transpose_67_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_68_perm_0 = const()[name = string("transpose_68_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_68 = transpose(perm = transpose_68_perm_0, x = var_639_cast_fp16)[name = string("transpose_82")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_67 = transpose(perm = transpose_67_perm_0, x = mul_9_cast_fp16)[name = string("transpose_83")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_9_cast_fp16 = matmul(transpose_x = matmul_9_transpose_x_0, transpose_y = matmul_9_transpose_y_0, x = transpose_67, y = transpose_68)[name = string("matmul_9_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_9_cast_fp16 = add(x = matmul_9_cast_fp16, y = var_57_to_fp16)[name = string("add_9_cast_fp16")]; |
| int32 softmax_9_axis_0 = const()[name = string("softmax_9_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_9_cast_fp16 = softmax(axis = softmax_9_axis_0, x = add_9_cast_fp16)[name = string("softmax_9_cast_fp16")]; |
| bool attn_output_37_transpose_x_0 = const()[name = string("attn_output_37_transpose_x_0"), val = bool(false)]; |
| bool attn_output_37_transpose_y_0 = const()[name = string("attn_output_37_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_39_cast_fp16 = transpose(perm = value_states_39_perm_0, x = var_642_cast_fp16)[name = string("transpose_84")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_37_cast_fp16 = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = softmax_9_cast_fp16, y = value_states_39_cast_fp16)[name = string("attn_output_37_cast_fp16")]; |
| tensor<int32, [4]> attn_output_39_perm_0 = const()[name = string("attn_output_39_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_646 = const()[name = string("op_646"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_39_cast_fp16 = transpose(perm = attn_output_39_perm_0, x = attn_output_37_cast_fp16)[name = string("transpose_81")]; |
| tensor<fp16, [1, 77, 768]> input_113_cast_fp16 = reshape(shape = var_646, x = attn_output_39_cast_fp16)[name = string("input_113_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(207159168)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(208338880)))]; |
| tensor<fp16, [1, 77, 768]> linear_57_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16, x = input_113_cast_fp16)[name = string("linear_57_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_115_cast_fp16 = add(x = input_111_cast_fp16, y = linear_57_cast_fp16)[name = string("input_115_cast_fp16")]; |
| tensor<int32, [1]> input_117_axes_0 = const()[name = string("input_117_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(208340480)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(208342080)))]; |
| tensor<fp16, [1, 77, 768]> input_117_cast_fp16 = layer_norm(axes = input_117_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_117_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(208343680)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(213062336)))]; |
| tensor<fp16, [1, 77, 3072]> linear_58_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16, x = input_117_cast_fp16)[name = string("linear_58_cast_fp16")]; |
| fp16 var_661_to_fp16 = const()[name = string("op_661_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_662_cast_fp16 = mul(x = linear_58_cast_fp16, y = var_661_to_fp16)[name = string("op_662_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_663_cast_fp16 = sigmoid(x = var_662_cast_fp16)[name = string("op_663_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_121_cast_fp16 = mul(x = linear_58_cast_fp16, y = var_663_cast_fp16)[name = string("input_121_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(213068544)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(217787200)))]; |
| tensor<fp16, [1, 77, 768]> linear_59_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16, x = input_121_cast_fp16)[name = string("linear_59_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_123_cast_fp16 = add(x = input_115_cast_fp16, y = linear_59_cast_fp16)[name = string("input_123_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_61_axes_0 = const()[name = string("hidden_states_61_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(217788800)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(217790400)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_61_cast_fp16 = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_123_cast_fp16)[name = string("hidden_states_61_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(217792000)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(218971712)))]; |
| tensor<fp16, [1, 77, 768]> linear_60_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16, x = hidden_states_61_cast_fp16)[name = string("linear_60_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(218973312)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(220153024)))]; |
| tensor<fp16, [1, 77, 768]> linear_61_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16, x = hidden_states_61_cast_fp16)[name = string("linear_61_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(220154624)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(221334336)))]; |
| tensor<fp16, [1, 77, 768]> linear_62_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16, x = hidden_states_61_cast_fp16)[name = string("linear_62_cast_fp16")]; |
| tensor<int32, [4]> var_693 = const()[name = string("op_693"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_694_cast_fp16 = reshape(shape = var_693, x = linear_60_cast_fp16)[name = string("op_694_cast_fp16")]; |
| tensor<int32, [4]> var_696 = const()[name = string("op_696"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_697_cast_fp16 = reshape(shape = var_696, x = linear_61_cast_fp16)[name = string("op_697_cast_fp16")]; |
| tensor<int32, [4]> var_699 = const()[name = string("op_699"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_700_cast_fp16 = reshape(shape = var_699, x = linear_62_cast_fp16)[name = string("op_700_cast_fp16")]; |
| tensor<int32, [4]> value_states_43_perm_0 = const()[name = string("value_states_43_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_10_cast_fp16 = mul(x = var_694_cast_fp16, y = var_17_to_fp16)[name = string("mul_10_cast_fp16")]; |
| bool matmul_10_transpose_y_0 = const()[name = string("matmul_10_transpose_y_0"), val = bool(true)]; |
| bool matmul_10_transpose_x_0 = const()[name = string("matmul_10_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_69_perm_0 = const()[name = string("transpose_69_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_70_perm_0 = const()[name = string("transpose_70_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_70 = transpose(perm = transpose_70_perm_0, x = var_697_cast_fp16)[name = string("transpose_78")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_69 = transpose(perm = transpose_69_perm_0, x = mul_10_cast_fp16)[name = string("transpose_79")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_10_cast_fp16 = matmul(transpose_x = matmul_10_transpose_x_0, transpose_y = matmul_10_transpose_y_0, x = transpose_69, y = transpose_70)[name = string("matmul_10_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_10_cast_fp16 = add(x = matmul_10_cast_fp16, y = var_57_to_fp16)[name = string("add_10_cast_fp16")]; |
| int32 softmax_10_axis_0 = const()[name = string("softmax_10_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_10_cast_fp16 = softmax(axis = softmax_10_axis_0, x = add_10_cast_fp16)[name = string("softmax_10_cast_fp16")]; |
| bool attn_output_41_transpose_x_0 = const()[name = string("attn_output_41_transpose_x_0"), val = bool(false)]; |
| bool attn_output_41_transpose_y_0 = const()[name = string("attn_output_41_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_43_cast_fp16 = transpose(perm = value_states_43_perm_0, x = var_700_cast_fp16)[name = string("transpose_80")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_41_cast_fp16 = matmul(transpose_x = attn_output_41_transpose_x_0, transpose_y = attn_output_41_transpose_y_0, x = softmax_10_cast_fp16, y = value_states_43_cast_fp16)[name = string("attn_output_41_cast_fp16")]; |
| tensor<int32, [4]> attn_output_43_perm_0 = const()[name = string("attn_output_43_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_704 = const()[name = string("op_704"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_43_cast_fp16 = transpose(perm = attn_output_43_perm_0, x = attn_output_41_cast_fp16)[name = string("transpose_77")]; |
| tensor<fp16, [1, 77, 768]> input_125_cast_fp16 = reshape(shape = var_704, x = attn_output_43_cast_fp16)[name = string("input_125_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(221335936)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(222515648)))]; |
| tensor<fp16, [1, 77, 768]> linear_63_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16, x = input_125_cast_fp16)[name = string("linear_63_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_127_cast_fp16 = add(x = input_123_cast_fp16, y = linear_63_cast_fp16)[name = string("input_127_cast_fp16")]; |
| tensor<int32, [1]> input_129_axes_0 = const()[name = string("input_129_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(222517248)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(222518848)))]; |
| tensor<fp16, [1, 77, 768]> input_129_cast_fp16 = layer_norm(axes = input_129_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_127_cast_fp16)[name = string("input_129_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(222520448)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(227239104)))]; |
| tensor<fp16, [1, 77, 3072]> linear_64_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16, x = input_129_cast_fp16)[name = string("linear_64_cast_fp16")]; |
| fp16 var_719_to_fp16 = const()[name = string("op_719_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_720_cast_fp16 = mul(x = linear_64_cast_fp16, y = var_719_to_fp16)[name = string("op_720_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_721_cast_fp16 = sigmoid(x = var_720_cast_fp16)[name = string("op_721_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_133_cast_fp16 = mul(x = linear_64_cast_fp16, y = var_721_cast_fp16)[name = string("input_133_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(227245312)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(231963968)))]; |
| tensor<fp16, [1, 77, 768]> linear_65_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16, x = input_133_cast_fp16)[name = string("linear_65_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_135_cast_fp16 = add(x = input_127_cast_fp16, y = linear_65_cast_fp16)[name = string("input_135_cast_fp16")]; |
| tensor<int32, [1]> hidden_states_67_axes_0 = const()[name = string("hidden_states_67_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(231965568)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(231967168)))]; |
| tensor<fp16, [1, 77, 768]> hidden_states_67_cast_fp16 = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_135_cast_fp16)[name = string("hidden_states_67_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(231968768)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(233148480)))]; |
| tensor<fp16, [1, 77, 768]> linear_66_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16, x = hidden_states_67_cast_fp16)[name = string("linear_66_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(233150080)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(234329792)))]; |
| tensor<fp16, [1, 77, 768]> linear_67_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16, x = hidden_states_67_cast_fp16)[name = string("linear_67_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(234331392)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235511104)))]; |
| tensor<fp16, [1, 77, 768]> linear_68_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16, x = hidden_states_67_cast_fp16)[name = string("linear_68_cast_fp16")]; |
| tensor<int32, [4]> var_751 = const()[name = string("op_751"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_752_cast_fp16 = reshape(shape = var_751, x = linear_66_cast_fp16)[name = string("op_752_cast_fp16")]; |
| tensor<int32, [4]> var_754 = const()[name = string("op_754"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_755_cast_fp16 = reshape(shape = var_754, x = linear_67_cast_fp16)[name = string("op_755_cast_fp16")]; |
| tensor<int32, [4]> var_757 = const()[name = string("op_757"), val = tensor<int32, [4]>([1, -1, 12, 64])]; |
| tensor<fp16, [1, 77, 12, 64]> var_758_cast_fp16 = reshape(shape = var_757, x = linear_68_cast_fp16)[name = string("op_758_cast_fp16")]; |
| tensor<int32, [4]> value_states_perm_0 = const()[name = string("value_states_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<fp16, [1, 77, 12, 64]> mul_11_cast_fp16 = mul(x = var_752_cast_fp16, y = var_17_to_fp16)[name = string("mul_11_cast_fp16")]; |
| bool matmul_11_transpose_y_0 = const()[name = string("matmul_11_transpose_y_0"), val = bool(true)]; |
| bool matmul_11_transpose_x_0 = const()[name = string("matmul_11_transpose_x_0"), val = bool(false)]; |
| tensor<int32, [4]> transpose_71_perm_0 = const()[name = string("transpose_71_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<int32, [4]> transpose_72_perm_0 = const()[name = string("transpose_72_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_72 = transpose(perm = transpose_72_perm_0, x = var_755_cast_fp16)[name = string("transpose_74")]; |
| tensor<fp16, [1, 12, 77, 64]> transpose_71 = transpose(perm = transpose_71_perm_0, x = mul_11_cast_fp16)[name = string("transpose_75")]; |
| tensor<fp16, [1, 12, 77, 77]> matmul_11_cast_fp16 = matmul(transpose_x = matmul_11_transpose_x_0, transpose_y = matmul_11_transpose_y_0, x = transpose_71, y = transpose_72)[name = string("matmul_11_cast_fp16")]; |
| tensor<fp16, [1, 12, 77, 77]> add_11_cast_fp16 = add(x = matmul_11_cast_fp16, y = var_57_to_fp16)[name = string("add_11_cast_fp16")]; |
| int32 softmax_11_axis_0 = const()[name = string("softmax_11_axis_0"), val = int32(-1)]; |
| tensor<fp16, [1, 12, 77, 77]> softmax_11_cast_fp16 = softmax(axis = softmax_11_axis_0, x = add_11_cast_fp16)[name = string("softmax_11_cast_fp16")]; |
| bool attn_output_45_transpose_x_0 = const()[name = string("attn_output_45_transpose_x_0"), val = bool(false)]; |
| bool attn_output_45_transpose_y_0 = const()[name = string("attn_output_45_transpose_y_0"), val = bool(false)]; |
| tensor<fp16, [1, 12, 77, 64]> value_states_cast_fp16 = transpose(perm = value_states_perm_0, x = var_758_cast_fp16)[name = string("transpose_76")]; |
| tensor<fp16, [1, 12, 77, 64]> attn_output_45_cast_fp16 = matmul(transpose_x = attn_output_45_transpose_x_0, transpose_y = attn_output_45_transpose_y_0, x = softmax_11_cast_fp16, y = value_states_cast_fp16)[name = string("attn_output_45_cast_fp16")]; |
| tensor<int32, [4]> attn_output_perm_0 = const()[name = string("attn_output_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])]; |
| tensor<int32, [3]> var_762 = const()[name = string("op_762"), val = tensor<int32, [3]>([1, 77, 768])]; |
| tensor<fp16, [1, 77, 12, 64]> attn_output_cast_fp16 = transpose(perm = attn_output_perm_0, x = attn_output_45_cast_fp16)[name = string("transpose_73")]; |
| tensor<fp16, [1, 77, 768]> input_137_cast_fp16 = reshape(shape = var_762, x = attn_output_cast_fp16)[name = string("input_137_cast_fp16")]; |
| tensor<fp16, [768, 768]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235512704)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(236692416)))]; |
| tensor<fp16, [1, 77, 768]> linear_69_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16, x = input_137_cast_fp16)[name = string("linear_69_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_139_cast_fp16 = add(x = input_135_cast_fp16, y = linear_69_cast_fp16)[name = string("input_139_cast_fp16")]; |
| tensor<int32, [1]> input_141_axes_0 = const()[name = string("input_141_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(236694016)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(236695616)))]; |
| tensor<fp16, [1, 77, 768]> input_141_cast_fp16 = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_139_cast_fp16)[name = string("input_141_cast_fp16")]; |
| tensor<fp16, [3072, 768]> text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(236697216)))]; |
| tensor<fp16, [3072]> text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(241415872)))]; |
| tensor<fp16, [1, 77, 3072]> linear_70_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16, x = input_141_cast_fp16)[name = string("linear_70_cast_fp16")]; |
| fp16 var_777_to_fp16 = const()[name = string("op_777_to_fp16"), val = fp16(0x1.b3cp+0)]; |
| tensor<fp16, [1, 77, 3072]> var_778_cast_fp16 = mul(x = linear_70_cast_fp16, y = var_777_to_fp16)[name = string("op_778_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> var_779_cast_fp16 = sigmoid(x = var_778_cast_fp16)[name = string("op_779_cast_fp16")]; |
| tensor<fp16, [1, 77, 3072]> input_145_cast_fp16 = mul(x = linear_70_cast_fp16, y = var_779_cast_fp16)[name = string("input_145_cast_fp16")]; |
| tensor<fp16, [768, 3072]> text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(241422080)))]; |
| tensor<fp16, [768]> text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = string("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(246140736)))]; |
| tensor<fp16, [1, 77, 768]> linear_71_cast_fp16 = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16, x = input_145_cast_fp16)[name = string("linear_71_cast_fp16")]; |
| tensor<fp16, [1, 77, 768]> input_cast_fp16 = add(x = input_139_cast_fp16, y = linear_71_cast_fp16)[name = string("input_cast_fp16")]; |
| tensor<int32, [1]> last_hidden_state_axes_0 = const()[name = string("last_hidden_state_axes_0"), val = tensor<int32, [1]>([-1])]; |
| tensor<fp16, [768]> text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = string("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(246142336)))]; |
| tensor<fp16, [768]> text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = string("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(246143936)))]; |
| tensor<fp16, [1, 77, 768]> last_hidden_state_cast_fp16 = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias_to_fp16, epsilon = var_15_to_fp16, gamma = text_encoder_text_model_final_layer_norm_weight_to_fp16, x = input_cast_fp16)[name = string("last_hidden_state_cast_fp16")]; |
| string last_hidden_state_cast_fp16_to_fp32_dtype_0 = const()[name = string("last_hidden_state_cast_fp16_to_fp32_dtype_0"), val = string("fp32")]; |
| tensor<int32, [1]> var_790 = const()[name = string("op_790"), val = tensor<int32, [1]>([0])]; |
| int32 var_792_axis_0 = const()[name = string("op_792_axis_0"), val = int32(-1)]; |
| bool var_792_keep_dims_0 = const()[name = string("op_792_keep_dims_0"), val = bool(false)]; |
| string var_792_output_dtype_0 = const()[name = string("op_792_output_dtype_0"), val = string("int32")]; |
| tensor<int32, [1]> var_792 = reduce_argmax(axis = var_792_axis_0, keep_dims = var_792_keep_dims_0, output_dtype = var_792_output_dtype_0, x = cast_1)[name = string("op_792")]; |
| int32 stack_0_axis_0 = const()[name = string("stack_0_axis_0"), val = int32(1)]; |
| tensor<int32, [1, 2]> stack_0 = stack(axis = stack_0_axis_0, values = (var_790, var_792))[name = string("stack_0")]; |
| int32 var_794_transpose_batch_dims_0 = const()[name = string("op_794_transpose_batch_dims_0"), val = int32(0)]; |
| bool var_794_transpose_validate_indices_0 = const()[name = string("op_794_transpose_validate_indices_0"), val = bool(false)]; |
| string stack_0_to_uint16_dtype_0 = const()[name = string("stack_0_to_uint16_dtype_0"), val = string("uint16")]; |
| tensor<uint16, [1, 2]> stack_0_to_uint16 = cast(dtype = stack_0_to_uint16_dtype_0, x = stack_0)[name = string("cast_54")]; |
| tensor<fp16, [1, 768]> var_794_transpose_cast_fp16_cast_uint16 = gather_nd(batch_dims = var_794_transpose_batch_dims_0, indices = stack_0_to_uint16, validate_indices = var_794_transpose_validate_indices_0, x = last_hidden_state_cast_fp16)[name = string("op_794_transpose_cast_fp16_cast_uint16")]; |
| string var_794_cast_fp16_to_fp32_dtype_0 = const()[name = string("op_794_cast_fp16_to_fp32_dtype_0"), val = string("fp32")]; |
| tensor<fp32, [1, 768]> pooled_outputs = cast(dtype = var_794_cast_fp16_to_fp32_dtype_0, x = var_794_transpose_cast_fp16_cast_uint16)[name = string("cast_53")]; |
| tensor<fp32, [1, 77, 768]> last_hidden_state = cast(dtype = last_hidden_state_cast_fp16_to_fp32_dtype_0, x = last_hidden_state_cast_fp16)[name = string("cast_55")]; |
| } -> (last_hidden_state, pooled_outputs); |
| } |
