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Validate some shape requirements for Conv3DBackpropFilter* and Conv3DBackpropInput* ops. #49350

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May 20, 2021
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Validate some shape requirements for Conv3DBackpropFilter* and Conv3DBackpropInput* ops. #49350

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56 changes: 56 additions & 0 deletions tensorflow/core/kernels/conv_grad_ops_3d.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -238,6 +238,20 @@ class Conv3DBackpropInputOp : public OpKernel {
input_shape = context->input(0).shape();
}

OP_REQUIRES(
context, input_shape.dim_size(4) == filter_shape.dim_size(3),
errors::InvalidArgument("input and filter_sizes must have the same "
"number of channels. Got ",
input_shape.dim_size(4), " for input and ",
filter_shape.dim_size(3), " for filter_sizes"));
OP_REQUIRES(
context, out_backprop_shape.dim_size(4) == filter_shape.dim_size(4),
errors::InvalidArgument("out_backprop and filter_sizes must have the "
"same number of channels. Got ",
out_backprop_shape.dim_size(4),
" for out_backprop and ",
filter_shape.dim_size(4), " for filter_sizes"));

ConvBackpropDimensions dims;
OP_REQUIRES_OK(context, ConvBackpropComputeDimensions(
"Conv3DBackpropInputOp", /*num_spatial_dims=*/3,
Expand Down Expand Up @@ -345,6 +359,20 @@ class Conv3DCustomBackpropInputOp : public OpKernel {
input_shape = context->input(0).shape();
}

OP_REQUIRES(
context, input_shape.dim_size(4) == filter_shape.dim_size(3),
errors::InvalidArgument("input and filter_sizes must have the same "
"number of channels. Got ",
input_shape.dim_size(4), " for input and ",
filter_shape.dim_size(3), " for filter_sizes"));
OP_REQUIRES(
context, out_backprop_shape.dim_size(4) == filter_shape.dim_size(4),
errors::InvalidArgument("out_backprop and filter_sizes must have the "
"same number of channels. Got ",
out_backprop_shape.dim_size(4),
" for out_backprop and ",
filter_shape.dim_size(4), " for filter_sizes"));

ConvBackpropDimensions dims;
OP_REQUIRES_OK(context, ConvBackpropComputeDimensions(
"Conv3DBackpropInputOp", /*num_spatial_dims=*/3,
Expand Down Expand Up @@ -695,6 +723,20 @@ class Conv3DBackpropFilterOp : public OpKernel {
filter_shape = context->input(1).shape();
}

OP_REQUIRES(
context, input_shape.dim_size(4) == filter_shape.dim_size(3),
errors::InvalidArgument("input and filter_sizes must have the same "
"number of channels. Got ",
input_shape.dim_size(4), " for input and ",
filter_shape.dim_size(3), " for filter_sizes"));
OP_REQUIRES(
context, out_backprop_shape.dim_size(4) == filter_shape.dim_size(4),
errors::InvalidArgument("out_backprop and filter_sizes must have the "
"same number of channels. Got ",
out_backprop_shape.dim_size(4),
" for out_backprop and ",
filter_shape.dim_size(4), " for filter_sizes"));

ConvBackpropDimensions dims;
OP_REQUIRES_OK(context,
ConvBackpropComputeDimensions(
Expand Down Expand Up @@ -807,6 +849,20 @@ class Conv3DCustomBackpropFilterOp : public OpKernel {
filter_shape = context->input(1).shape();
}

OP_REQUIRES(
context, input_shape.dim_size(4) == filter_shape.dim_size(3),
errors::InvalidArgument("input and filter_sizes must have the same "
"number of channels. Got ",
input_shape.dim_size(4), " for input and ",
filter_shape.dim_size(3), " for filter_sizes"));
OP_REQUIRES(
context, out_backprop_shape.dim_size(4) == filter_shape.dim_size(4),
errors::InvalidArgument("out_backprop and filter_sizes must have the "
"same number of channels. Got ",
out_backprop_shape.dim_size(4),
" for out_backprop and ",
filter_shape.dim_size(4), " for filter_sizes"));

ConvBackpropDimensions dims;
OP_REQUIRES_OK(context,
ConvBackpropComputeDimensions(
Expand Down