def __init__(self, delta, inputs, filters, fprop, **kwargs):
"""
Arguments:
inputs : input tensor.
filters : filter/kernel tensor.
"""
super(bprop_conv,
self).__init__(args=(ContiguousOp(delta), ContiguousOp(filters)),
fprop=fprop,
axes=inputs.axes,
**kwargs)
def visit(self, op, input1, input2):
replace = False
if not isinstance(input1, ContiguousOp):
input1 = ContiguousOp(input1)
replace = True
if not isinstance(input2, ContiguousOp):
input2 = ContiguousOp(input2)
replace = True
if replace:
self.replace_op(op, Add(input1, input2))
def visit(self, op, inputs):
"""
MKLDNN Pooling implementation requires contiguous layout.
"""
if not isinstance(inputs, ContiguousOp):
new_op = PoolingOp(op.pool_params, ContiguousOp(inputs), axes=op.axes)
self.replace_op(op, new_op)
def visit(self, op):
"""
Convolution implementation requires contiguous layout.
"""
inputs, filters = op.args
replace = False
if not isinstance(inputs, ContiguousOp):
inputs = ContiguousOp(inputs)
replace = True
if not isinstance(filters, ContiguousOp):
filters = ContiguousOp(filters)
replace = True
if replace:
self.replace_op(
op, ConvolutionOp(op.conv_params,
inputs,
filters,
axes=op.axes))
def visit(self, op, *args):
"""
Warp-CTC requires all args to be contiguous
"""
args = list(args)
replace = False
for ii, arg in enumerate(args):
if not is_contiguous(arg):
args[ii] = ContiguousOp(arg)
replace = True
if replace is True:
self.replace_op(op, CTCOp(*args, axes=op.axes))
def visit(self, op, delta, inputs, dbias=None):
replace = False
# If we have updated op.fprop in this pass, replace this op
# with a version with the replaced fprop.
fprop = op.fprop
replacement_fprop = self.get_replacement(fprop)
if replacement_fprop is not None:
replace = True
fprop = replacement_fprop
if not isinstance(delta, ContiguousOp):
delta = ContiguousOp(delta)
replace = True
# if not isinstance(inputs, ContiguousOp):
# inputs = ContiguousOp(inputs)
# replace = True
if replace:
self.replace_op(op, update_conv(delta, inputs, self.op_arg(fprop, 1), fprop, op.dbias))