/usr/local/lib64/python3.6/site-packages/caffe2/python
Edit: /usr/local/lib64/python3.6/site-packages/caffe2/python/cnn.py (7626B)
## @package cnn
# Module caffe2.python.cnn
from caffe2.python import brew, workspace
from caffe2.python.model_helper import ModelHelper
from caffe2.proto import caffe2_pb2
import logging
class CNNModelHelper(ModelHelper):
"""A helper model so we can write CNN models more easily, without having to
manually define parameter initializations and operators separately.
"""
def __init__(self, order="NCHW", name=None,
use_cudnn=True, cudnn_exhaustive_search=False,
ws_nbytes_limit=None, init_params=True,
skip_sparse_optim=False,
param_model=None):
logging.warning(
"[====DEPRECATE WARNING====]: you are creating an "
"object from CNNModelHelper class which will be deprecated soon. "
"Please use ModelHelper object with brew module. For more "
"information, please refer to caffe2.ai and python/brew.py, "
"python/brew_test.py for more information."
)
cnn_arg_scope = {
'order': order,
'use_cudnn': use_cudnn,
'cudnn_exhaustive_search': cudnn_exhaustive_search,
}
if ws_nbytes_limit:
cnn_arg_scope['ws_nbytes_limit'] = ws_nbytes_limit
super(CNNModelHelper, self).__init__(
skip_sparse_optim=skip_sparse_optim,
name="CNN" if name is None else name,
init_params=init_params,
param_model=param_model,
arg_scope=cnn_arg_scope,
)
self.order = order
self.use_cudnn = use_cudnn
self.cudnn_exhaustive_search = cudnn_exhaustive_search
self.ws_nbytes_limit = ws_nbytes_limit
if self.order != "NHWC" and self.order != "NCHW":
raise ValueError(
"Cannot understand the CNN storage order %s." % self.order
)
def ImageInput(self, blob_in, blob_out, use_gpu_transform=False, **kwargs):
return brew.image_input(
self,
blob_in,
blob_out,
order=self.order,
use_gpu_transform=use_gpu_transform,
**kwargs
)
def VideoInput(self, blob_in, blob_out, **kwargs):
return brew.video_input(
self,
blob_in,
blob_out,
**kwargs
)
def PadImage(self, blob_in, blob_out, **kwargs):
# TODO(wyiming): remove this dummy helper later
self.net.PadImage(blob_in, blob_out, **kwargs)
def ConvNd(self, *args, **kwargs):
return brew.conv_nd(
self,
*args,
use_cudnn=self.use_cudnn,
order=self.order,
cudnn_exhaustive_search=self.cudnn_exhaustive_search,
ws_nbytes_limit=self.ws_nbytes_limit,
**kwargs
)
def Conv(self, *args, **kwargs):
return brew.conv(
self,
*args,
use_cudnn=self.use_cudnn,
order=self.order,
cudnn_exhaustive_search=self.cudnn_exhaustive_search,
ws_nbytes_limit=self.ws_nbytes_limit,
**kwargs
)
def ConvTranspose(self, *args, **kwargs):
return brew.conv_transpose(
self,
*args,
use_cudnn=self.use_cudnn,
order=self.order,
cudnn_exhaustive_search=self.cudnn_exhaustive_search,
ws_nbytes_limit=self.ws_nbytes_limit,
**kwargs
)
def GroupConv(self, *args, **kwargs):
return brew.group_conv(
self,
*args,
use_cudnn=self.use_cudnn,
order=self.order,
cudnn_exhaustive_search=self.cudnn_exhaustive_search,
ws_nbytes_limit=self.ws_nbytes_limit,
**kwargs
)
def GroupConv_Deprecated(self, *args, **kwargs):
return brew.group_conv_deprecated(
self,
*args,
use_cudnn=self.use_cudnn,
order=self.order,
cudnn_exhaustive_search=self.cudnn_exhaustive_search,
ws_nbytes_limit=self.ws_nbytes_limit,
**kwargs
)
def FC(self, *args, **kwargs):
return brew.fc(self, *args, **kwargs)
def PackedFC(self, *args, **kwargs):
return brew.packed_fc(self, *args, **kwargs)
def FC_Prune(self, *args, **kwargs):
return brew.fc_prune(self, *args, **kwargs)
def FC_Decomp(self, *args, **kwargs):
return brew.fc_decomp(self, *args, **kwargs)
def FC_Sparse(self, *args, **kwargs):
return brew.fc_sparse(self, *args, **kwargs)
def Dropout(self, *args, **kwargs):
return brew.dropout(
self, *args, order=self.order, use_cudnn=self.use_cudnn, **kwargs
)
def LRN(self, *args, **kwargs):
return brew.lrn(
self, *args, order=self.order, use_cudnn=self.use_cudnn, **kwargs
)
def Softmax(self, *args, **kwargs):
return brew.softmax(self, *args, use_cudnn=self.use_cudnn, **kwargs)
def SpatialBN(self, *args, **kwargs):
return brew.spatial_bn(self, *args, order=self.order, **kwargs)
def SpatialGN(self, *args, **kwargs):
return brew.spatial_gn(self, *args, order=self.order, **kwargs)
def InstanceNorm(self, *args, **kwargs):
return brew.instance_norm(self, *args, order=self.order, **kwargs)
def Relu(self, *args, **kwargs):
return brew.relu(
self, *args, order=self.order, use_cudnn=self.use_cudnn, **kwargs
)
def PRelu(self, *args, **kwargs):
return brew.prelu(self, *args, **kwargs)
def Concat(self, *args, **kwargs):
return brew.concat(self, *args, order=self.order, **kwargs)
def DepthConcat(self, *args, **kwargs):
"""The old depth concat function - we should move to use concat."""
print("DepthConcat is deprecated. use Concat instead.")
return self.Concat(*args, **kwargs)
def Sum(self, *args, **kwargs):
return brew.sum(self, *args, **kwargs)
def Transpose(self, *args, **kwargs):
return brew.transpose(self, *args, use_cudnn=self.use_cudnn, **kwargs)
def Iter(self, *args, **kwargs):
return brew.iter(self, *args, **kwargs)
def Accuracy(self, *args, **kwargs):
return brew.accuracy(self, *args, **kwargs)
def MaxPool(self, *args, **kwargs):
return brew.max_pool(
self, *args, use_cudnn=self.use_cudnn, order=self.order, **kwargs
)
def MaxPoolWithIndex(self, *args, **kwargs):
return brew.max_pool_with_index(self, *args, order=self.order, **kwargs)
def AveragePool(self, *args, **kwargs):
return brew.average_pool(
self, *args, use_cudnn=self.use_cudnn, order=self.order, **kwargs
)
@property
def XavierInit(self):
return ('XavierFill', {})
def ConstantInit(self, value):
return ('ConstantFill', dict(value=value))
@property
def MSRAInit(self):
return ('MSRAFill', {})
@property
def ZeroInit(self):
return ('ConstantFill', {})
def AddWeightDecay(self, weight_decay):
return brew.add_weight_decay(self, weight_decay)
@property
def CPU(self):
device_option = caffe2_pb2.DeviceOption()
device_option.device_type = caffe2_pb2.CPU
return device_option
@property
def GPU(self, gpu_id=0):
device_option = caffe2_pb2.DeviceOption()
device_option.device_type = workspace.GpuDeviceType
device_option.device_id = gpu_id
return device_option