prompt stringlengths 94 42.6k | completion stringlengths 6 120 | api stringlengths 14 68 |
|---|---|---|
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.log(gt_height / bbox_height) | megengine.functional.log |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.stack([target_dx, target_dy, target_dw, target_dh], axis=1) | megengine.functional.stack |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(inter / union, 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(inter / union, 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(inter / b_area_box, 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(inter / union, 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.equal(gt[:, 4], ignore_label) | megengine.functional.equal |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(ignore_mask, 0) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.exp(dw) | megengine.functional.exp |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.exp(dh) | megengine.functional.exp |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(box, 1) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(gt, 0) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.minimum(b_box[:, :, 2], b_gt[:, :, 2]) | megengine.functional.minimum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.minimum(b_box[:, :, 3], b_gt[:, :, 3]) | megengine.functional.minimum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(iw, 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(ih, 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(box[:, 2] - box[:, 0], 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(box[:, 3] - box[:, 1], 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(gt[:, 2] - gt[:, 0], 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(gt[:, 3] - gt[:, 1], 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(area_box, 1) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(area_gt, 0) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(box, 1) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(gt, 0) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.minimum(b_box[:, :, 2], b_gt[:, :, 2]) | megengine.functional.minimum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.minimum(b_box[:, :, 3], b_gt[:, :, 3]) | megengine.functional.minimum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(iw, 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(ih, 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(box[:, 2] - box[:, 0], 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(box[:, 3] - box[:, 1], 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(gt[:, 2] - gt[:, 0], 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.maximum(gt[:, 3] - gt[:, 1], 0) | megengine.functional.maximum |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(area_gt, 0) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(area_box, 1) | megengine.functional.expand_dims |
import math
import megengine as mge
import megengine.functional as F
import numpy as np
from megengine import Tensor
import pdb
def restore_bbox(rois, deltas, unnormalize=True, config = None):
assert deltas.ndim == 3
if unnormalize:
std_opr = mge.tensor(config.bbox_normalize_stds.reshape(1, 1, -1))
... | F.expand_dims(rois, 1) | megengine.functional.expand_dims |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | sqrt(bn_var + eps) | megengine.functional.sqrt |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Tensor(opr.weight) | megengine.Tensor |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Tensor(opr.inp_tensors[1].np_data) | megengine.Tensor |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Tensor(opr.bias) | megengine.Tensor |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Tensor(opr.inp_tensors[2].np_data) | megengine.Tensor |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Tensor(opr.mean) | megengine.Tensor |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Tensor(opr.inp_tensors[3].np_data) | megengine.Tensor |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Tensor(opr.var) | megengine.Tensor |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Tensor(opr.inp_tensors[4].np_data) | megengine.Tensor |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.ones((1, 3, 3, 3)) | megengine.functional.ones |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | trace_module(module, x) | megengine.traced_module.trace_module |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.copy(x) | megengine.functional.copy |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Node._set_next_id(159) | megengine.traced_module.node.Node._set_next_id |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | Expr._set_next_id(1024) | megengine.traced_module.expr.Expr._set_next_id |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | trace_module(module, x) | megengine.traced_module.trace_module |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | trace_module(module, x) | megengine.traced_module.trace_module |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | M.Conv2d(in_channels, channels, 3, 1, padding=1, bias=False) | megengine.module.Conv2d |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | M.BatchNorm2d(channels) | megengine.module.BatchNorm2d |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.concat([a, a]) | megengine.functional.concat |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.neg(relu_out) | megengine.functional.neg |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.zeros((1,)) | megengine.functional.zeros |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | qat.Concat() | megengine.module.qat.Concat |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.concat([expect, expect, expect]) | megengine.functional.concat |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.relu(x) | megengine.functional.relu |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | M.Identity() | megengine.module.Identity |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.zeros((1,)) | megengine.functional.zeros |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.neg(relu_out) | megengine.functional.neg |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | M.Identity() | megengine.module.Identity |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | M.Identity() | megengine.module.Identity |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | M.Identity() | megengine.module.Identity |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | M.Identity() | megengine.module.Identity |
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY ... | F.neg(x) | megengine.functional.neg |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | Elemwise(mode) | megengine.core.ops.builtin.Elemwise |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | dist.Server(port) | megengine.distributed.Server |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper([0.0]) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(y_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(dz_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(dz_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | Elemwise(Elemwise.Mode.RELU) | megengine.core.ops.builtin.Elemwise |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorAttr() | megengine.core._imperative_rt.TensorAttr |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | imperative.make_backward_graph(op, [attr], [True], [True]) | megengine.core._imperative_rt.imperative.make_backward_graph |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | F.broadcast_to(x, (3, 3, 10)) | megengine.functional.broadcast_to |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | TensorWrapper(x_np) | megengine.core.tensor.tensor_wrapper.TensorWrapper |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | apply(op, *args) | megengine.core.tensor.tensor.apply |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | dist.get_free_ports(1) | megengine.distributed.get_free_ports |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | dist.init_process_group("localhost", port, world_size, 0, 0) | megengine.distributed.init_process_group |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | mge.device.set_default_device("gpu0") | megengine.device.set_default_device |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | Grad() | megengine.core.autodiff.grad.Grad |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | remote_send(x, 1) | megengine.functional.distributed.remote_send |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | remote_recv(1, x_np.shape, x_np.dtype, "gpu0") | megengine.functional.distributed.remote_recv |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | dist.init_process_group("localhost", port, world_size, 1, 1) | megengine.distributed.init_process_group |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | mge.device.set_default_device("gpu1") | megengine.device.set_default_device |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | Grad() | megengine.core.autodiff.grad.Grad |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | remote_recv(0, x_np.shape, x_np.dtype, "gpu1") | megengine.functional.distributed.remote_recv |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT ARRANTI... | remote_send(recv_x, 0) | megengine.functional.distributed.remote_send |
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