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!11055 unified Tensor type of graph mode and pynative mode in timedistributed 

From: @dinglongwei
Reviewed-by: @c_34,@wuxuejian
Signed-off-by: @c_34
This commit is contained in:
mindspore-ci-bot 2021-01-07 19:35:06 +08:00 committed by Gitee
parent 19f3d0d038 d9d53a7710
commit 78d51aa323
1 changed files with 3 additions and 10 deletions
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13
mindspore/nn/layer/timedistributed.py
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@ -16,7 +16,6 @@
from mindspore.ops.primitive import constexpr, Primitive
from mindspore.ops import Reshape, Transpose, Pack, Unpack
from mindspore.common.dtype import tensor
from mindspore.common import Tensor
from ..cell import Cell
@ -105,9 +104,7 @@ class TimeDistributed(Cell):
self.reshape = Reshape()
def construct(self, inputs):
is_capital_tensor = isinstance(inputs, Tensor)
is_tensor = True if is_capital_tensor else isinstance(inputs, tensor)
_check_data(is_tensor)
_check_data(isinstance(inputs, Tensor))
_check_inputs_dim(inputs.shape)
time_axis = self.time_axis % len(inputs.shape)
if self.reshape_with_axis is not None:
@ -122,9 +119,7 @@ class TimeDistributed(Cell):
inputs_shape_new = inputs.shape
inputs = self.reshape(inputs, inputs_shape_new[: reshape_pos] + (-1,) + inputs_shape_new[reshape_pos + 2:])
outputs = self.layer(inputs)
is_capital_tensor = isinstance(outputs, Tensor)
is_tensor = True if is_capital_tensor else isinstance(outputs, tensor)
_check_data(is_tensor)
_check_data(isinstance(outputs, Tensor))
_check_reshape_pos(reshape_pos, inputs.shape, outputs.shape)
outputs_shape_new = outputs.shape[:reshape_pos] + inputs_shape_new[reshape_pos: reshape_pos + 2]
if reshape_pos + 1 < len(outputs.shape):
@ -136,9 +131,7 @@ class TimeDistributed(Cell):
y = ()
for item in inputs:
outputs = self.layer(item)
is_capital_tensor = isinstance(outputs, Tensor)
is_tensor = True if is_capital_tensor else isinstance(outputs, tensor)
_check_data(is_tensor)
_check_data(isinstance(outputs, Tensor))
_check_expand_dims_axis(time_axis, outputs.ndim)
y += (outputs,)
y = Pack(time_axis)(y)