prompt stringlengths 94 42.6k | completion stringlengths 6 120 | api stringlengths 14 68 |
|---|---|---|
# -*- 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... | fake_quant_tensor(x, qmin, qmax, q_dict) | megengine.quantization.utils.fake_quant_tensor |
# -*- 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... | tensor(inp_data, dtype=np.float32) | megengine.tensor |
# -*- 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... | make_shape_tuple(x.grad.shape) | megengine.core.tensor.utils.make_shape_tuple |
# -*- 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... | make_shape_tuple(x1.grad.shape) | megengine.core.tensor.utils.make_shape_tuple |
# -*- 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... | fake_quant_tensor(inp, qmin, qmax, q_dict) | megengine.quantization.utils.fake_quant_tensor |
# -*- 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... | Grad() | megengine.core.autodiff.grad.Grad |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.reshape(x, (n, c, -1, k1 * k2)) | megengine.functional.reshape |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.transpose(x, (0, 1, 3, 2)) | megengine.functional.transpose |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.reshape(x, (n, c * k1 * k2, -1)) | megengine.functional.reshape |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.reshape(mask, (N, 1, 9, rate, rate, H, W)) | megengine.functional.reshape |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.softmax(mask, axis=2) | megengine.functional.softmax |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.reshape(up_flow, (N, 2, 9, 1, 1, H, W)) | megengine.functional.reshape |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.sum(mask * up_flow, axis=2) | megengine.functional.sum |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.transpose(up_flow, (0, 1, 4, 2, 5, 3)) | megengine.functional.transpose |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.reshape(up_flow, (N, 2, rate * H, rate * W)) | megengine.functional.reshape |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.zeros([N, 1, H, W], dtype="float32") | megengine.functional.zeros |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.zeros([N, 1, H, W], dtype="float32") | megengine.functional.zeros |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | amp.autocast(enabled=self.mixed_precision) | megengine.amp.autocast |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | amp.autocast(enabled=self.mixed_precision) | megengine.amp.autocast |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.avg_pool2d(fmap1, 2, stride=2) | megengine.functional.avg_pool2d |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.avg_pool2d(fmap2, 2, stride=2) | megengine.functional.avg_pool2d |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.split(fmap1, [hdim], axis=1) | megengine.functional.split |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.tanh(net) | megengine.functional.tanh |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.relu(inp) | megengine.functional.relu |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.avg_pool2d(net, 2, stride=2) | megengine.functional.avg_pool2d |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.avg_pool2d(inp, 2, stride=2) | megengine.functional.avg_pool2d |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.avg_pool2d(fmap1, 4, stride=4) | megengine.functional.avg_pool2d |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.avg_pool2d(fmap2, 4, stride=4) | megengine.functional.avg_pool2d |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.avg_pool2d(net, 4, stride=4) | megengine.functional.avg_pool2d |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.avg_pool2d(inp, 4, stride=4) | megengine.functional.avg_pool2d |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.concat([_x, _y], axis=1) | megengine.functional.concat |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.transpose(x_tmp, (0, 2, 3, 1)) | megengine.functional.transpose |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.transpose(x_tmp, (0, 2, 3, 1)) | megengine.functional.transpose |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | amp.autocast(enabled=self.mixed_precision) | megengine.amp.autocast |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.reshape(x, (x.shape[0], image1.shape[2] // 16, -1, x.shape[2])) | megengine.functional.reshape |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | amp.autocast(enabled=self.mixed_precision) | megengine.amp.autocast |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | amp.autocast(enabled=self.mixed_precision) | megengine.amp.autocast |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.sigmoid(offset_dw8) | megengine.functional.sigmoid |
import megengine.module as M
import megengine.functional as F
from megengine import amp
from .update import BasicUpdateBlock
from .extractor import BasicEncoder
from .corr import AGCL
from .attention import PositionEncodingSine, LocalFeatureTransformer
class CREStereo(M.Module):
def __init__(self, max_disp=192,... | F.sigmoid(offset_dw16) | megengine.functional.sigmoid |
# 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 ... | mge.load(traced_module) | megengine.load |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.BatchNorm2d(self.in_channels) | megengine.module.BatchNorm2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.BatchNorm2d(self.hidden_channels) | megengine.module.BatchNorm2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.ReLU() | megengine.module.ReLU |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.ReLU() | megengine.module.ReLU |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.Conv2d(self.in_channels, self.out_channels, 3, 1, 1) | megengine.module.Conv2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.Conv2d(self.out_channels, self.out_channels, 3, 1, 1) | megengine.module.Conv2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.Conv2d(self.in_channels, self.out_channels, 1, 1, 0) | megengine.module.Conv2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.ReLU() | megengine.module.ReLU |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.init.xavier_uniform_(self.c_sc.weight, 1.0) | megengine.module.init.xavier_uniform_ |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | F.avg_pool2d(h, 2) | megengine.functional.avg_pool2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.init.xavier_uniform_(self.c_sc.weight, 1.0) | megengine.module.init.xavier_uniform_ |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.Conv2d(in_channels, out_channels, 1, 1, 0) | megengine.module.Conv2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | M.init.xavier_uniform_(self.c_sc.weight, 1.0) | megengine.module.init.xavier_uniform_ |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | F.avg_pool2d(h, 2) | megengine.functional.avg_pool2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | F.avg_pool2d(x, 2) | megengine.functional.avg_pool2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | F.avg_pool2d(x, 2) | megengine.functional.avg_pool2d |
# Copyright (c) 2020 <NAME>
# This code is licensed under MIT license
# (https://github.com/kwotsin/mimicry/blob/master/LICENSE)
# ------------------------------------------------------------------------------
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 Megv... | F.relu(x) | megengine.functional.relu |
#!/usr/bin/env python
# -*-coding=utf-8-*-
from megengine.logger import get_logger
logger = | get_logger(__name__) | megengine.logger.get_logger |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.is_distributed() | megengine.distributed.is_distributed |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.is_distributed() | megengine.distributed.is_distributed |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.all_reduce_sum(loss) | megengine.distributed.all_reduce_sum |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.get_world_size() | megengine.distributed.get_world_size |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.all_reduce_sum(acc1) | megengine.distributed.all_reduce_sum |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.get_world_size() | megengine.distributed.get_world_size |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.all_reduce_sum(acc5) | megengine.distributed.all_reduce_sum |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.get_world_size() | megengine.distributed.get_world_size |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.all_reduce_sum(loss) | megengine.distributed.all_reduce_sum |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.get_world_size() | megengine.distributed.get_world_size |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.all_reduce_sum(acc1) | megengine.distributed.all_reduce_sum |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.get_world_size() | megengine.distributed.get_world_size |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.all_reduce_sum(acc5) | megengine.distributed.all_reduce_sum |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.get_world_size() | megengine.distributed.get_world_size |
# -*- coding: utf-8 -*-
# MIT License
#
# Copyright (c) 2019 Megvii Technology
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
#... | dist.get_rank() | megengine.distributed.get_rank |
# 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 ... | mge.load(traced_module) | megengine.load |
import numpy as np
from megengine import tensor
def _default_compare_fn(x, y):
np.testing.assert_allclose(x.numpy(), y, rtol=1e-6)
def opr_test(cases, func, compare_fn=_default_compare_fn, ref_fn=None, **kwargs):
"""
:param cases: the list which have dict element, the list length should be 2 for dynami... | tensor(inpi) | megengine.tensor |
from itertools import product
import numpy as np
from megengine import tensor
from megengine.module import (
Conv2d,
ConvBn2d,
ConvRelu2d,
DequantStub,
Module,
QuantStub,
)
from megengine.quantization.quantize import disable_fake_quant, quantize_qat
def test_qat_convbn2d():
in_channels =... | quantize_qat(module, inplace=False) | megengine.quantization.quantize.quantize_qat |
from itertools import product
import numpy as np
from megengine import tensor
from megengine.module import (
Conv2d,
ConvBn2d,
ConvRelu2d,
DequantStub,
Module,
QuantStub,
)
from megengine.quantization.quantize import disable_fake_quant, quantize_qat
def test_qat_convbn2d():
in_channels =... | disable_fake_quant(qat_module) | megengine.quantization.quantize.disable_fake_quant |
from itertools import product
import numpy as np
from megengine import tensor
from megengine.module import (
Conv2d,
ConvBn2d,
ConvRelu2d,
DequantStub,
Module,
QuantStub,
)
from megengine.quantization.quantize import disable_fake_quant, quantize_qat
def test_qat_convbn2d():
in_channels =... | quantize_qat(net, inplace=False) | megengine.quantization.quantize.quantize_qat |
from itertools import product
import numpy as np
from megengine import tensor
from megengine.module import (
Conv2d,
ConvBn2d,
ConvRelu2d,
DequantStub,
Module,
QuantStub,
)
from megengine.quantization.quantize import disable_fake_quant, quantize_qat
def test_qat_convbn2d():
in_channels =... | disable_fake_quant(qat_net) | megengine.quantization.quantize.disable_fake_quant |
from itertools import product
import numpy as np
from megengine import tensor
from megengine.module import (
Conv2d,
ConvBn2d,
ConvRelu2d,
DequantStub,
Module,
QuantStub,
)
from megengine.quantization.quantize import disable_fake_quant, quantize_qat
def test_qat_convbn2d():
in_channels =... | QuantStub() | megengine.module.QuantStub |
from itertools import product
import numpy as np
from megengine import tensor
from megengine.module import (
Conv2d,
ConvBn2d,
ConvRelu2d,
DequantStub,
Module,
QuantStub,
)
from megengine.quantization.quantize import disable_fake_quant, quantize_qat
def test_qat_convbn2d():
in_channels =... | DequantStub() | megengine.module.DequantStub |
#!/usr/bin/env python3
# Copyright (c) 2020 <NAME>
# This file has been modified by Megvii ("Megvii Modifications").
# All Megvii Modifications are Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
"""LARS optimizer
References: https://github.com/rwightman/pytorch-image-models/blob/master/timm/optim/lars.py
"""... | tensor(lr) | megengine.tensor |
#!/usr/bin/env python3
# Copyright (c) 2020 <NAME>
# This file has been modified by Megvii ("Megvii Modifications").
# All Megvii Modifications are Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
"""LARS optimizer
References: https://github.com/rwightman/pytorch-image-models/blob/master/timm/optim/lars.py
"""... | tensor(weight_decay) | megengine.tensor |
#!/usr/bin/env python3
# Copyright (c) 2020 <NAME>
# This file has been modified by Megvii ("Megvii Modifications").
# All Megvii Modifications are Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
"""LARS optimizer
References: https://github.com/rwightman/pytorch-image-models/blob/master/timm/optim/lars.py
"""... | tensor(momentum) | megengine.tensor |
#!/usr/bin/env python3
# Copyright (c) 2020 <NAME>
# This file has been modified by Megvii ("Megvii Modifications").
# All Megvii Modifications are Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
"""LARS optimizer
References: https://github.com/rwightman/pytorch-image-models/blob/master/timm/optim/lars.py
"""... | tensor(-lr) | megengine.tensor |
#!/usr/bin/env python3
# Copyright (c) 2020 <NAME>
# This file has been modified by Megvii ("Megvii Modifications").
# All Megvii Modifications are Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
"""LARS optimizer
References: https://github.com/rwightman/pytorch-image-models/blob/master/timm/optim/lars.py
"""... | F.sum(vec * vec) | megengine.functional.sum |
#!/usr/bin/env python3
# Copyright (c) 2020 <NAME>
# This file has been modified by Megvii ("Megvii Modifications").
# All Megvii Modifications are Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
"""LARS optimizer
References: https://github.com/rwightman/pytorch-image-models/blob/master/timm/optim/lars.py
"""... | _inplace_add_(param, grad, alpha=c1, beta=_neg_lr * trust_ratio) | megengine.functional.inplace._inplace_add_ |
#!/usr/bin/env python3
# Copyright (c) 2020 <NAME>
# This file has been modified by Megvii ("Megvii Modifications").
# All Megvii Modifications are Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
"""LARS optimizer
References: https://github.com/rwightman/pytorch-image-models/blob/master/timm/optim/lars.py
"""... | _inplace_add_(v, grad, alpha=_momentum, beta=c1) | megengine.functional.inplace._inplace_add_ |
import os
import megengine as mge
import megengine.functional as F
import argparse
import numpy as np
import cv2
from nets import Model
def load_model(model_path):
print("Loading model:", os.path.abspath(model_path))
pretrained_dict = | mge.load(model_path) | megengine.load |
import os
import megengine as mge
import megengine.functional as F
import argparse
import numpy as np
import cv2
from nets import Model
def load_model(model_path):
print("Loading model:", os.path.abspath(model_path))
pretrained_dict = mge.load(model_path)
model = Model(max_disp=256, mixed_precision=Fals... | mge.tensor(imgL) | megengine.tensor |
import os
import megengine as mge
import megengine.functional as F
import argparse
import numpy as np
import cv2
from nets import Model
def load_model(model_path):
print("Loading model:", os.path.abspath(model_path))
pretrained_dict = mge.load(model_path)
model = Model(max_disp=256, mixed_precision=Fals... | mge.tensor(imgR) | megengine.tensor |
import os
import megengine as mge
import megengine.functional as F
import argparse
import numpy as np
import cv2
from nets import Model
def load_model(model_path):
print("Loading model:", os.path.abspath(model_path))
pretrained_dict = mge.load(model_path)
model = Model(max_disp=256, mixed_precision=Fals... | F.squeeze(pred_flow[:, 0, :, :]) | megengine.functional.squeeze |
import os
import cv2
import argparse
import warnings
import megengine as mge
import megengine.functional as F
warnings.filterwarnings("ignore")
parser = argparse.ArgumentParser(description='Interpolation for a pair of images')
parser.add_argument('--img', dest='img', nargs=2, required=True)
parser.add_argument('--exp'... | F.nn.pad(img0, padding) | megengine.functional.nn.pad |
import os
import cv2
import argparse
import warnings
import megengine as mge
import megengine.functional as F
warnings.filterwarnings("ignore")
parser = argparse.ArgumentParser(description='Interpolation for a pair of images')
parser.add_argument('--img', dest='img', nargs=2, required=True)
parser.add_argument('--exp'... | F.nn.pad(img1, padding) | megengine.functional.nn.pad |
# -*- 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... | hub.pretrained(
"https://data.megengine.org.cn/models/weights/mspn_4stage_256x192_0_255_75_2.pkl"
) | megengine.hub.pretrained |
# -*- 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... | M.Sequential(*layers) | megengine.module.Sequential |
# -*- 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... | M.Conv2d(channel, mid_channel, 1, 1, 0) | megengine.module.Conv2d |
# -*- 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... | M.ConvTranspose2d(mid_channel, mid_channel, 4, 2, 1) | megengine.module.ConvTranspose2d |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.