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# -*- coding: utf-8 -*-
# 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 ARRANTI... | T.ToMode() | megengine.data.transform.ToMode |
import logging
from megengine.distributed.group import get_rank
from megengine.distributed import is_distributed
logger_initialized = {}
def get_logger(name, log_file=None, log_level=logging.INFO):
"""Initialize and get a logger by name.
If the logger has not been initialized, this method will initialize the... | is_distributed() | megengine.distributed.is_distributed |
import logging
from megengine.distributed.group import get_rank
from megengine.distributed import is_distributed
logger_initialized = {}
def get_logger(name, log_file=None, log_level=logging.INFO):
"""Initialize and get a logger by name.
If the logger has not been initialized, this method will initialize the... | is_distributed() | megengine.distributed.is_distributed |
import logging
from megengine.distributed.group import get_rank
from megengine.distributed import is_distributed
logger_initialized = {}
def get_logger(name, log_file=None, log_level=logging.INFO):
"""Initialize and get a logger by name.
If the logger has not been initialized, this method will initialize the... | get_rank() | megengine.distributed.group.get_rank |
import logging
from megengine.distributed.group import get_rank
from megengine.distributed import is_distributed
logger_initialized = {}
def get_logger(name, log_file=None, log_level=logging.INFO):
"""Initialize and get a logger by name.
If the logger has not been initialized, this method will initialize the... | get_rank() | megengine.distributed.group.get_rank |
import argparse
import logging
import os
import dataset.data_loader as data_loader
import model.net as net
from common import utils
from loss.losses import compute_losses, compute_metrics
from common.manager import Manager
import megengine.distributed as dist
import megengine.functional as F
parser = argparse.Argum... | dist.get_rank() | megengine.distributed.get_rank |
import argparse
import logging
import os
import dataset.data_loader as data_loader
import model.net as net
from common import utils
from loss.losses import compute_losses, compute_metrics
from common.manager import Manager
import megengine.distributed as dist
import megengine.functional as F
parser = argparse.Argum... | dist.get_world_size() | megengine.distributed.get_world_size |
import argparse
import logging
import os
import dataset.data_loader as data_loader
import model.net as net
from common import utils
from loss.losses import compute_losses, compute_metrics
from common.manager import Manager
import megengine.distributed as dist
import megengine.functional as F
parser = argparse.Argum... | F.distributed.all_reduce_sum(v) | megengine.functional.distributed.all_reduce_sum |
import argparse
import logging
import os
import dataset.data_loader as data_loader
import model.net as net
from common import utils
from loss.losses import compute_losses, compute_metrics
from common.manager import Manager
import megengine.distributed as dist
import megengine.functional as F
parser = argparse.Argum... | F.distributed.all_reduce_sum(v) | megengine.functional.distributed.all_reduce_sum |
import argparse
import logging
import os
import dataset.data_loader as data_loader
import model.net as net
from common import utils
from loss.losses import compute_losses, compute_metrics
from common.manager import Manager
import megengine.distributed as dist
import megengine.functional as F
parser = argparse.Argum... | F.distributed.all_reduce_sum(v) | megengine.functional.distributed.all_reduce_sum |
import argparse
import logging
import os
import dataset.data_loader as data_loader
import model.net as net
from common import utils
from loss.losses import compute_losses, compute_metrics
from common.manager import Manager
import megengine.distributed as dist
import megengine.functional as F
parser = argparse.Argum... | F.distributed.all_reduce_sum(v) | megengine.functional.distributed.all_reduce_sum |
import sys
sys.path.append('.')
import cv2
import megengine as mge
import megengine.functional as F
import numpy as np
from model.RIFE import Model
model = Model()
model.load_model('train_log')
model.eval()
name = ['Beanbags', 'Dimetrodon', 'DogDance', 'Grove2', 'Grove3', 'Hydrangea', 'MiniCooper', 'RubberWhale', 'Ur... | F.zeros([1, 6, 480, 640]) | megengine.functional.zeros |
import sys
sys.path.append('.')
import cv2
import megengine as mge
import megengine.functional as F
import numpy as np
from model.RIFE import Model
model = Model()
model.load_model('train_log')
model.eval()
name = ['Beanbags', 'Dimetrodon', 'DogDance', 'Grove2', 'Grove3', 'Hydrangea', 'MiniCooper', 'RubberWhale', 'Ur... | mge.Tensor(i0) | megengine.Tensor |
import sys
sys.path.append('.')
import cv2
import megengine as mge
import megengine.functional as F
import numpy as np
from model.RIFE import Model
model = Model()
model.load_model('train_log')
model.eval()
name = ['Beanbags', 'Dimetrodon', 'DogDance', 'Grove2', 'Grove3', 'Hydrangea', 'MiniCooper', 'RubberWhale', 'Ur... | mge.Tensor(i1) | megengine.Tensor |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | F.sqrt(running_var + eps) | megengine.functional.sqrt |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | F.conv2d(beta - running_mean * gamma / std, kernel, conv.bias) | megengine.functional.conv2d |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | F.flatten(conv.weight, end_axis=conv.weight.ndim - 4) | megengine.functional.flatten |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | F.sqrt(running_var + eps) | megengine.functional.sqrt |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.Dropout(drop) | megengine.module.Dropout |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.BatchNorm2d(channels) | megengine.module.BatchNorm2d |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.BatchNorm2d(channels) | megengine.module.BatchNorm2d |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.BatchNorm2d(dims[-1]) | megengine.module.BatchNorm2d |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.AdaptiveAvgPool2d(1) | megengine.module.AdaptiveAvgPool2d |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | F.flatten(x, 1) | megengine.functional.flatten |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.Identity() | megengine.module.Identity |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.Linear(dims[-1], num_classes) | megengine.module.Linear |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.Identity() | megengine.module.Identity |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | F.pad(dw_small.weight, [[0, 0]] * 3 + [[(kernel - k) // 2] * 2] * 2) | megengine.functional.pad |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.Identity() | megengine.module.Identity |
# Copyright (c) 2014-2022 Megvii Inc. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eithe... | nn.Identity() | megengine.module.Identity |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = | nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias) | megengine.module.Conv2d |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = | nn.Conv2d(in_chn, out_chn, kernel_size=4, stride=2, padding=1, bias=bias) | megengine.module.Conv2d |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.Conv2d(in_size, out_size, kernel_size=1, bias=True) | megengine.module.Conv2d |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.ConvTranspose2d(in_size, out_size, kernel_size=2, stride=2, bias=True) | megengine.module.ConvTranspose2d |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | F.concat([up, bridge], 1) | megengine.functional.concat |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.Conv2d(in_size, out_size, kernel_size=1, bias=True) | megengine.module.Conv2d |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.Conv2d(in_size, out_size, kernel_size=1, bias=True) | megengine.module.Conv2d |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.Conv2d(in_size, out_size, kernel_size=3, padding=1, bias=True) | megengine.module.Conv2d |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.LeakyReLU(relu_slope) | megengine.module.LeakyReLU |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.Conv2d(out_size, out_size, kernel_size=3, padding=1, bias=True) | megengine.module.Conv2d |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.LeakyReLU(relu_slope) | megengine.module.LeakyReLU |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | F.matmul(V_t, V) | megengine.functional.matmul |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | F.matinv(mat) | megengine.functional.matinv |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | F.matmul(mat_inv, V_t) | megengine.functional.matmul |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | F.concat([up, bridge], 1) | megengine.functional.concat |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.init.xavier_uniform_(m.weight) | megengine.module.init.xavier_uniform_ |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | nn.init.zeros_(m.bias) | megengine.module.init.zeros_ |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | F.abs(V_t) | megengine.functional.abs |
#!/usr/bin/env python3
import megengine as mge
import megengine.module as nn
import megengine.functional as F
def conv3x3(in_chn, out_chn, bias=True):
layer = nn.Conv2d(in_chn, out_chn, kernel_size=3, stride=1, padding=1, bias=bias)
return layer
def conv_down(in_chn, out_chn, bias=False):
layer = nn.Conv... | F.matmul(V, project_feature) | megengine.functional.matmul |
# -*- coding: utf-8 -*-
# This repo 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 ... | mge.load(self.params.restore_file) | megengine.load |
# -*- coding: utf-8 -*-
# This repo 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 ... | mge.save(state, latest_ckpt_name) | megengine.save |
# -*- coding: utf-8 -*-
# This repo 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 ... | mge.save(state, best_ckpt_name) | megengine.save |
# -*- coding: utf-8 -*-
# This repo 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 ... | mge.save(state, best_ckpt_name) | megengine.save |
# 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 ... | mgb.dtype.qint8(self.scale) | megengine._internal.dtype.qint8 |
# 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 ... | mgb.dtype.get_scale(inp.dtype) | megengine._internal.dtype.get_scale |
# 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 ... | mgb.dtype.get_scale(self.weight.dtype) | megengine._internal.dtype.get_scale |
# 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 ... | mgb.dtype.qint32(self.scale) | megengine._internal.dtype.qint32 |
# 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 ... | mgb.dtype.qint32(bias_scale) | megengine._internal.dtype.qint32 |
# -*- 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([4, 4]) | 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... | tensor([4, 4]) | 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... | tensor(2) | 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... | tensor(4) | megengine.tensor |
import sys
sys.path.append('.')
import time
import megengine as mge
from model.RIFE import Model
model = Model()
model.eval()
I0 = | mge.random(1, 3, 480, 640) | megengine.random |
import sys
sys.path.append('.')
import time
import megengine as mge
from model.RIFE import Model
model = Model()
model.eval()
I0 = mge.random(1, 3, 480, 640)
I1 = | mge.random(1, 3, 480, 640) | megengine.random |
import sys
sys.path.append('.')
import time
import megengine as mge
from model.RIFE import Model
model = Model()
model.eval()
I0 = mge.random(1, 3, 480, 640)
I1 = mge.random(1, 3, 480, 640)
for i in range(100):
pred = model.inference(I0, I1)
| mge._full_sync() | megengine._full_sync |
import sys
sys.path.append('.')
import time
import megengine as mge
from model.RIFE import Model
model = Model()
model.eval()
I0 = mge.random(1, 3, 480, 640)
I1 = mge.random(1, 3, 480, 640)
for i in range(100):
pred = model.inference(I0, I1)
mge._full_sync()
time_stamp = time.time()
for i in range(100):
pred ... | mge._full_sync() | megengine._full_sync |
# Copyright (c) Megvii, Inc. and its affiliates.
import megengine.functional as F
import megengine.module as M
from .head import get_head
from .loss import get_loss
from .resnet import get_backbone
from .stn import STN
class FaceRecognitionModel(M.Module):
"""combination of all building blocks, including backbo... | F.normalize(embedding, axis=1) | megengine.functional.normalize |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | mge.tensor(x, dtype="float32") | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | mge.tensor(s, dtype="float32") | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | mge.tensor(g_y, dtype="float32") | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | QuantDtypeMeta("test_qint8", None, "int8", qmin, qmax) | megengine.core.tensor.dtype.QuantDtypeMeta |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | tensor([1.0], dtype=np.float32) | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | tensor([4.0], dtype=np.float32) | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | mge.tensor(x, dtype="float32") | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | mge.tensor(s, dtype="float32") | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | mge.tensor(zero_point, dtype="float32") | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | mge.tensor(grad_s, dtype="float32") | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | mge.tensor(g_y, dtype="float32") | megengine.tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | Grad() | megengine.core.autodiff.grad.Grad |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 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 ARRANTI... | tqt_forward(-127, 127, x, s) | megengine.quantization.utils.tqt_forward |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | F.round(x) | megengine.functional.round |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | F.maximum(oup, qmin) | megengine.functional.maximum |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | create_qparams(QuantMode.ASYMMERTIC, test_dtype, scale, zero_point) | megengine.quantization.utils.create_qparams |
# -*- coding: utf-8 -*-
# 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 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) 2014-2021 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 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) 2014-2021 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 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) 2014-2021 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 ARRANTI... | F.full((1, 32, 3, 3), np.nan) | megengine.functional.full |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | Grad() | megengine.core.autodiff.grad.Grad |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 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 ARRANTI... | lsq_forward(-127, 127, x, s, zero_point, grad_s) | megengine.quantization.utils.lsq_forward |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | Grad() | megengine.core.autodiff.grad.Grad |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 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 ARRANTI... | fake_quant_tensor(x, qparams) | megengine.quantization.utils.fake_quant_tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | Grad() | megengine.core.autodiff.grad.Grad |
# -*- coding: utf-8 -*-
# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
#
# Copyright (c) 2014-2021 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 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) 2014-2021 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 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) 2014-2021 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 ARRANTI... | fake_quant_tensor(inp, qparams) | megengine.quantization.utils.fake_quant_tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | fake_quant_tensor(x, qparams) | megengine.quantization.utils.fake_quant_tensor |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | F.ones_like(x) | megengine.functional.ones_like |
# -*- coding: utf-8 -*-
# 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 ARRANTI... | F.ones_like(x1) | megengine.functional.ones_like |
# 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 ... | mgb.dtype.get_scale(inp.dtype) | megengine._internal.dtype.get_scale |
# 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 ... | mgb.dtype.get_scale(self.weight.dtype) | megengine._internal.dtype.get_scale |
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