mirror of
https://github.com/zebrajr/pytorch.git
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033ab9da1b
Summary: Adding a simple video data layer which allows to read video data from frames, videos and output 5D tensor. It also allows multiple labels. The current implementation is based on ffmpeg Differential Revision: D4801798 fbshipit-source-id: 46448e9c65fb055c2d71855447383a33ade0e444
96 lines
2.9 KiB
Python
96 lines
2.9 KiB
Python
## @package model_helper_api
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# Module caffe2.python.model_helper_api
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import sys
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import copy
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# flake8: noqa
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from caffe2.python.helpers.dropout import *
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from caffe2.python.helpers.arg_scope import *
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from caffe2.python.helpers.fc import *
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from caffe2.python.helpers.pooling import *
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from caffe2.python.helpers.normalization import *
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from caffe2.python.helpers.nonlinearity import *
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from caffe2.python.helpers.array_helpers import *
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from caffe2.python.helpers.algebra import *
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from caffe2.python.helpers.train import *
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from caffe2.python.helpers.conv import *
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from caffe2.python.helpers.tools import *
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class HelperWrapper(object):
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_registry = {
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'arg_scope': arg_scope,
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'fc': fc,
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'packed_fc': packed_fc,
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'fc_decomp': fc_decomp,
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'fc_sparse': fc_sparse,
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'fc_prune': fc_prune,
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'dropout': dropout,
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'max_pool': max_pool,
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'average_pool': average_pool,
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'lrn': lrn,
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'softmax': softmax,
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'instance_norm': instance_norm,
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'spatial_bn': spatial_bn,
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'relu': relu,
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'prelu': prelu,
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'concat': concat,
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'depth_concat': depth_concat,
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'sum': sum,
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'transpose': transpose,
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'iter': iter,
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'accuracy': accuracy,
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'conv': conv,
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'conv_nd': conv_nd,
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'conv_transpose': conv_transpose,
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'group_conv': group_conv,
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'group_conv_deprecated': group_conv_deprecated,
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'image_input': image_input,
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'video_input': video_input,
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'add_weight_decay': add_weight_decay,
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}
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def __init__(self, wrapped):
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self.wrapped = wrapped
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def __getattr__(self, helper_name):
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if helper_name not in self._registry:
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raise AttributeError(
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"Helper function {} not "
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"registered.".format(helper_name)
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)
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def scope_wrapper(*args, **kwargs):
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cur_scope = get_current_scope()
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new_kwargs = copy.deepcopy(cur_scope.get(helper_name, {}))
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new_kwargs.update(kwargs)
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return self._registry[helper_name](*args, **new_kwargs)
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scope_wrapper.__name__ = helper_name
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return scope_wrapper
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def Register(self, helper):
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name = helper.__name__
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if name in self._registry:
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raise AttributeError(
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"Helper {} already exists. Please change your "
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"helper name.".format(name)
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)
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self._registry[name] = helper
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def has_helper(self, helper_or_helper_name):
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helper_name = (
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helper_or_helper_name
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if isinstance(helper_or_helper_name, basestring) else
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helper_or_helper_name.__name__
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)
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return helper_name in self._registry
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sys.modules[__name__] = HelperWrapper(sys.modules[__name__])
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