[OpAttr]Adapt tensor output_size for conv2d_transpose and depthwise_conv2d_transpose (#45620)

Adapt tensor output_size for conv2d_transpose and depthwise_conv2d_transpose

paddle/fluid/operators/conv_transpose_op.cc

@@ -121,7 +121,8 @@ void Conv2DTransposeOpMaker::Make() {
   AddAttr<std::vector<int>>("output_size",
                             "(vector<int> default: []), the "
                             "size of the output tensor")
-      .SetDefault({});
+      .SetDefault({})
+      .SupportTensor();
   AddAttr<int>("groups",
                "(int default:1), the groups number of the convolution "
                "transpose operator. ")
@@ -398,10 +399,10 @@ namespace ops = paddle::operators;
 // conv2d_transpose
 DECLARE_INFER_SHAPE_FUNCTOR(conv2d_transpose,
                             Conv2dTranposeInferShapeFunctor,
-                            PD_INFER_META(phi::ConvTransposeInferMeta));
+                            PD_INFER_META(phi::Conv2dTransposeInferMeta));
 DECLARE_INFER_SHAPE_FUNCTOR(conv2d_transpose_grad,
                             Conv2dTranposeGradInferShapeFunctor,
-                            PD_INFER_META(phi::ConvTransposeGradInferMeta));
+                            PD_INFER_META(phi::Conv2dTransposeGradInferMeta));
 DECLARE_INFER_SHAPE_FUNCTOR(
     conv2d_transpose_grad_grad,
     Conv2dTranposeDoubleGradInferShapeFunctor,
@@ -443,10 +444,10 @@ REGISTER_OPERATOR(conv3d_transpose_grad,
 // depthwise conv2d_transpose
 DECLARE_INFER_SHAPE_FUNCTOR(depthwise_conv2d_transpose,
                             DepthWiseConv2dTranposeInferShapeFunctor,
-                            PD_INFER_META(phi::ConvTransposeInferMeta));
+                            PD_INFER_META(phi::Conv2dTransposeInferMeta));
 DECLARE_INFER_SHAPE_FUNCTOR(depthwise_conv2d_transpose_grad,
                             DepthWiseConv2dTranposeGradInferShapeFunctor,
-                            PD_INFER_META(phi::ConvTransposeGradInferMeta));
+                            PD_INFER_META(phi::Conv2dTransposeGradInferMeta));
 
 REGISTER_OPERATOR(depthwise_conv2d_transpose,
                   ops::ConvTransposeOp,

paddle/phi/api/yaml/legacy_api.yaml

@@ -541,10 +541,10 @@
   backward : conv2d_grad
 
 - api : conv2d_transpose
-  args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
+  args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
   output : Tensor(out)
   infer_meta :
-    func : ConvTransposeInferMeta
+    func : Conv2dTransposeInferMeta
   kernel :
     func : conv2d_transpose
     use_gpudnn : true
@@ -665,10 +665,10 @@
   backward : depthwise_conv2d_grad
 
 - api : depthwise_conv2d_transpose
-  args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
+  args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
   output : Tensor(out)
   infer_meta :
-    func : ConvTransposeInferMeta
+    func : Conv2dTransposeInferMeta
   kernel :
     func : depthwise_conv2d_transpose
   backward : depthwise_conv2d_transpose_grad

paddle/phi/api/yaml/legacy_backward.yaml

@@ -483,8 +483,8 @@
   optional : grad_input_grad, grad_filter_grad
 
 - backward_api : conv2d_transpose_double_grad
-  forward : conv2d_transpose_grad(Tensor x, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(grad_x), Tensor(grad_filter)
-  args : (Tensor x, Tensor filter, Tensor grad_out, Tensor grad_x_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
+  forward : conv2d_transpose_grad(Tensor x, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(grad_x), Tensor(grad_filter)
+  args : (Tensor x, Tensor filter, Tensor grad_out, Tensor grad_x_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
   output : Tensor(x_grad), Tensor(filter_grad), Tensor(grad_out_grad)
   infer_meta :
     func : Conv2dTransposeDoubleGradInferMeta
@@ -493,11 +493,11 @@
     use_gpudnn : true
 
 - backward_api : conv2d_transpose_grad
-  forward : conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
-  args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
+  forward : conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
+  args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
   output : Tensor(x_grad), Tensor(filter_grad)
   infer_meta :
-    func : ConvTransposeGradInferMeta
+    func : Conv2dTransposeGradInferMeta
   kernel :
     func : conv2d_transpose_grad
     use_gpudnn : true
@@ -635,11 +635,11 @@
   optional : grad_input_grad, grad_filter_grad
 
 - backward_api : depthwise_conv2d_transpose_grad
-  forward : depthwise_conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
-  args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
+  forward : depthwise_conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
+  args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
   output : Tensor(x_grad), Tensor(filter_grad)
   infer_meta :
-    func : ConvTransposeGradInferMeta
+    func : Conv2dTransposeGradInferMeta
   kernel :
     func : depthwise_conv2d_transpose_grad
 

paddle/phi/infermeta/backward.cc

@@ -143,6 +143,22 @@ void ConvTransposeGradInferMeta(const MetaTensor& x,
   GeneralBinaryGradInferMeta(x, filter, dx, dfilter);
 }
 
+void Conv2dTransposeGradInferMeta(const MetaTensor& x,
+                                  const MetaTensor& filter,
+                                  const MetaTensor& dout,
+                                  const std::vector<int>& strides,
+                                  const std::vector<int>& paddings,
+                                  const std::vector<int>& output_padding,
+                                  const IntArray& output_size,
+                                  const std::string& padding_algorithm,
+                                  int groups,
+                                  const std::vector<int>& dilations,
+                                  const std::string& data_format,
+                                  MetaTensor* dx,
+                                  MetaTensor* dfilter) {
+  GeneralBinaryGradInferMeta(x, filter, dx, dfilter);
+}
+
 void Conv2dTransposeDoubleGradInferMeta(const MetaTensor& x,
                                         const MetaTensor& filter,
                                         const MetaTensor& dout,
@@ -151,7 +167,7 @@ void Conv2dTransposeDoubleGradInferMeta(const MetaTensor& x,
                                         const std::vector<int>& strides,
                                         const std::vector<int>& paddings,
                                         const std::vector<int>& output_padding,
-                                        const std::vector<int>& output_size,
+                                        const IntArray& output_size,
                                         const std::string& padding_algorithm,
                                         int groups,
                                         const std::vector<int>& dilations,

paddle/phi/infermeta/backward.h

@@ -76,6 +76,20 @@ void ConvTransposeGradInferMeta(const MetaTensor& x,
                                 MetaTensor* dx,
                                 MetaTensor* dfilter);
 
+void Conv2dTransposeGradInferMeta(const MetaTensor& x,
+                                  const MetaTensor& filter,
+                                  const MetaTensor& dout,
+                                  const std::vector<int>& strides,
+                                  const std::vector<int>& paddings,
+                                  const std::vector<int>& output_padding,
+                                  const IntArray& output_size,
+                                  const std::string& padding_algorithm,
+                                  int groups,
+                                  const std::vector<int>& dilations,
+                                  const std::string& data_format,
+                                  MetaTensor* dx,
+                                  MetaTensor* dfilter);
+
 void Conv2dTransposeDoubleGradInferMeta(const MetaTensor& x,
                                         const MetaTensor& filter,
                                         const MetaTensor& dout,
@@ -84,7 +98,7 @@ void Conv2dTransposeDoubleGradInferMeta(const MetaTensor& x,
                                         const std::vector<int>& strides,
                                         const std::vector<int>& paddings,
                                         const std::vector<int>& output_padding,
-                                        const std::vector<int>& output_size,
+                                        const IntArray& output_size,
                                         const std::string& padding_algorithm,
                                         int groups,
                                         const std::vector<int>& dilations,

paddle/phi/infermeta/binary.cc

@@ -800,6 +800,34 @@ void ConvTransposeInferMeta(const MetaTensor& x,
   out->set_dtype(x.dtype());
 }
 
+void Conv2dTransposeInferMeta(const MetaTensor& x,
+                              const MetaTensor& filter,
+                              const std::vector<int>& strides,
+                              const std::vector<int>& paddings,
+                              const std::vector<int>& output_padding,
+                              const IntArray& output_size,
+                              const std::string& padding_algorithm,
+                              int groups,
+                              const std::vector<int>& dilations,
+                              const std::string& data_format,
+                              MetaTensor* out,
+                              MetaConfig config) {
+  std::vector<int32_t> vec_output_size(output_size.GetData().begin(),
+                                       output_size.GetData().end());
+  ConvTransposeInferMeta(x,
+                         filter,
+                         strides,
+                         paddings,
+                         output_padding,
+                         vec_output_size,
+                         padding_algorithm,
+                         groups,
+                         dilations,
+                         data_format,
+                         out,
+                         config);
+}
+
 void CrossInferMeta(const MetaTensor& x,
                     const MetaTensor& y,
                     int axis,

paddle/phi/infermeta/binary.h

@@ -119,6 +119,19 @@ void ConvTransposeInferMeta(const MetaTensor& x,
                             MetaTensor* out,
                             MetaConfig config = MetaConfig());
 
+void Conv2dTransposeInferMeta(const MetaTensor& x,
+                              const MetaTensor& filter,
+                              const std::vector<int>& strides,
+                              const std::vector<int>& paddings,
+                              const std::vector<int>& output_padding,
+                              const IntArray& output_size,
+                              const std::string& padding_algorithm,
+                              int groups,
+                              const std::vector<int>& dilations,
+                              const std::string& data_format,
+                              MetaTensor* out,
+                              MetaConfig config = MetaConfig());
+
 void CrossInferMeta(const MetaTensor& x,
                     const MetaTensor& y,
                     int axis,

paddle/phi/kernels/conv_transpose_grad_kernel.h

@@ -17,6 +17,7 @@
 #include <string>
 #include <vector>
 
+#include "paddle/phi/common/int_array.h"
 #include "paddle/phi/core/dense_tensor.h"
 
 namespace phi {
@@ -29,7 +30,7 @@ void Conv2dTransposeGradKernel(const Context& ctx,
                                const std::vector<int>& strides,
                                const std::vector<int>& paddings,
                                const std::vector<int>& output_padding,
-                               const std::vector<int>& output_size,
+                               const IntArray& output_size,
                                const std::string& padding_algorithm,
                                int groups,
                                const std::vector<int>& dilations,
@@ -47,7 +48,7 @@ void Conv2dTransposeDoubleGradKernel(const Context& ctx,
                                      const std::vector<int>& strides,
                                      const std::vector<int>& paddings,
                                      const std::vector<int>& output_padding,
-                                     const std::vector<int>& output_size,
+                                     const IntArray& output_size,
                                      const std::string& padding_algorithm,
                                      int groups,
                                      const std::vector<int>& dilations,
@@ -80,7 +81,7 @@ void DepthwiseConv2dTransposeGradKernel(const Context& ctx,
                                         const std::vector<int>& strides,
                                         const std::vector<int>& paddings,
                                         const std::vector<int>& output_padding,
-                                        const std::vector<int>& output_size,
+                                        const IntArray& output_size,
                                         const std::string& padding_algorithm,
                                         int groups,
                                         const std::vector<int>& dilations,

paddle/phi/kernels/conv_transpose_kernel.h

@@ -17,6 +17,7 @@
 #include <string>
 #include <vector>
 
+#include "paddle/phi/common/int_array.h"
 #include "paddle/phi/core/dense_tensor.h"
 
 namespace phi {
@@ -28,7 +29,7 @@ void Conv2dTransposeKernel(const Context& ctx,
                            const std::vector<int>& strides,
                            const std::vector<int>& paddings,
                            const std::vector<int>& output_padding,
-                           const std::vector<int>& output_size,
+                           const IntArray& output_size,
                            const std::string& padding_algorithm,
                            int groups,
                            const std::vector<int>& dilations,
@@ -56,7 +57,7 @@ void DepthwiseConv2dTransposeKernel(const Context& ctx,
                                     const std::vector<int>& strides,
                                     const std::vector<int>& paddings,
                                     const std::vector<int>& output_padding,
-                                    const std::vector<int>& output_size,
+                                    const IntArray& output_size,
                                     const std::string& padding_algorithm,
                                     int groups,
                                     const std::vector<int>& dilations,

paddle/phi/kernels/cpu/conv_transpose_grad_kernel.cc

@@ -27,7 +27,7 @@ void DepthwiseConv2dTransposeGradKernel(const Context& ctx,
                                         const std::vector<int>& strides,
                                         const std::vector<int>& paddings,
                                         const std::vector<int>& output_padding,
-                                        const std::vector<int>& output_size,
+                                        const IntArray& output_size,
                                         const std::string& padding_algorithm,
                                         int groups,
                                         const std::vector<int>& dilations,

paddle/phi/kernels/cpu/conv_transpose_kernel.cc

@@ -26,7 +26,7 @@ void DepthwiseConv2dTransposeKernel(const Context& ctx,
                                     const std::vector<int>& strides,
                                     const std::vector<int>& paddings,
                                     const std::vector<int>& output_padding,
-                                    const std::vector<int>& output_size,
+                                    const IntArray& output_size,
                                     const std::string& padding_algorithm,
                                     int groups,
                                     const std::vector<int>& dilations,

paddle/phi/kernels/gpu/conv_transpose_grad_kernel.cu

@@ -34,7 +34,7 @@ void Conv2dTransposeDoubleGradKernel(const Context& ctx,
                                      const std::vector<int>& strides,
                                      const std::vector<int>& paddings,
                                      const std::vector<int>& output_padding,
-                                     const std::vector<int>& output_size,
+                                     const IntArray& output_size,
                                      const std::string& padding_algorithm,
                                      int groups,
                                      const std::vector<int>& dilations,
@@ -64,7 +64,7 @@ void DepthwiseConv2dTransposeGradKernel(const Context& ctx,
                                         const std::vector<int>& strides,
                                         const std::vector<int>& paddings,
                                         const std::vector<int>& output_padding,
-                                        const std::vector<int>& output_size,
+                                        const IntArray& output_size,
                                         const std::string& padding_algorithm,
                                         int groups,
                                         const std::vector<int>& dilations,

paddle/phi/kernels/gpu/conv_transpose_kernel.cu

@@ -31,7 +31,7 @@ void DepthwiseConv2dTransposeKernel(const Context& ctx,
                                     const std::vector<int>& strides,
                                     const std::vector<int>& paddings,
                                     const std::vector<int>& output_padding,
-                                    const std::vector<int>& output_size,
+                                    const IntArray& output_size,
                                     const std::string& padding_algorithm,
                                     int groups,
                                     const std::vector<int>& dilations,

paddle/phi/kernels/gpudnn/conv_transpose_grad_kernel.cu

@@ -383,7 +383,7 @@ void Conv2dTransposeGradGPUDNNKernel(const Context& ctx,
                                      const std::vector<int>& strides,
                                      const std::vector<int>& paddings_,
                                      const std::vector<int>& output_padding,
-                                     const std::vector<int>& output_size,
+                                     const IntArray& output_size,
                                      const std::string& padding_algorithm,
                                      int groups,
                                      const std::vector<int>& dilations_,
@@ -422,7 +422,7 @@ void Conv2dTransposeDoubleGradGPUDNNKernel(
     const std::vector<int>& strides,
     const std::vector<int>& paddings,
     const std::vector<int>& output_padding,
-    const std::vector<int>& output_size,
+    const IntArray& output_size,
     const std::string& padding_algorithm,
     int groups,
     const std::vector<int>& dilations,

paddle/phi/kernels/gpudnn/conv_transpose_kernel.cu

@@ -308,7 +308,7 @@ void Conv2dTransposeGPUDNNKernel(const Context& ctx,
                                  const std::vector<int>& strides,
                                  const std::vector<int>& paddings,
                                  const std::vector<int>& output_padding,
-                                 const std::vector<int>& output_size,
+                                 const IntArray& output_size,
                                  const std::string& padding_algorithm,
                                  int groups,
                                  const std::vector<int>& dilations,

paddle/phi/kernels/impl/conv_transpose_grad_kernel_impl.h

@@ -310,7 +310,7 @@ void Conv2dTransposeGradKernel(const Context& ctx,
                                const std::vector<int>& strides,
                                const std::vector<int>& paddings,
                                const std::vector<int>& output_padding,
-                               const std::vector<int>& output_size,
+                               const IntArray& output_size,
                                const std::string& padding_algorithm,
                                int groups,
                                const std::vector<int>& dilations,

paddle/phi/kernels/impl/conv_transpose_kernel_impl.h

@@ -231,7 +231,7 @@ void Conv2dTransposeKernel(const Context& ctx,
                            const std::vector<int>& strides,
                            const std::vector<int>& paddings,
                            const std::vector<int>& output_padding,
-                           const std::vector<int>& output_size,
+                           const IntArray& output_size,
                            const std::string& padding_algorithm,
                            int groups,
                            const std::vector<int>& dilations,

paddle/phi/kernels/xpu/conv_transpose_grad_kernel.cc

@@ -27,7 +27,7 @@ void Conv2dTransposeGradKernel(const Context& ctx,
                                const std::vector<int>& strides,
                                const std::vector<int>& paddings,
                                const std::vector<int>& output_padding,
-                               const std::vector<int>& output_size,
+                               const IntArray& output_size,
                                const std::string& padding_algorithm,
                                int groups,
                                const std::vector<int>& dilations,

paddle/phi/kernels/xpu/conv_transpose_kernel.cc

@@ -42,7 +42,7 @@ void Conv2dTransposeKernel(const Context& ctx,
                            const std::vector<int>& strides,
                            const std::vector<int>& paddings,
                            const std::vector<int>& output_padding,
-                           const std::vector<int>& output_size,
+                           const IntArray& output_size,
                            const std::string& padding_algorithm,
                            int groups,
                            const std::vector<int>& dilations,

python/paddle/fluid/dygraph/nn.py

@@ -2717,12 +2717,29 @@ class Conv2DTranspose(layers.Layer):
 
         if self._output_size is None:
             self._output_size = []
-        elif isinstance(self._output_size, list) or isinstance(
-                self._output_size, int):
+        elif isinstance(self._output_size, list):
+            if utils._contain_var(self._output_size):
+                self._output_size = utils._convert_to_tensor_list(
+                    self._output_size)
+            else:
+                self._output_size = utils.convert_to_list(
+                    self._output_size, 2, 'output_size')
+        elif isinstance(self._output_size, int):
             self._output_size = utils.convert_to_list(self._output_size, 2,
                                                       'output_size')
+        elif isinstance(self._output_size, Variable):
+            check_dtype(self._output_size.dtype, 'output_size',
+                        ['int32', 'int64'], 'Conv2DTranspose')
+            if len(self._output_size.shape) == 1 and (
+                    self._output_size.shape[0] == 1
+                    or self._output_size.shape[0] == 2):
+                if self._output_size.shape[0] == 1:
+                    self._output_size = [self._output_size, self._output_size]
+            else:
+                raise ValueError(
+                    "output_size must contain one or two integers.")
         else:
-            raise ValueError("output_size should be list or int")
+            raise ValueError("output_size should be list or int or Tensor")
         self._padding = utils.convert_to_list(self._padding, 2, 'padding')
         self._groups = 1 if self._groups is None else self._groups
         filter_shape = [self._num_channels, self._num_filters // self._groups

python/paddle/fluid/layers/nn.py

@@ -4216,11 +4216,42 @@ def conv2d_transpose(input,
 
     padding = _update_padding(padding, data_format)
 
-    if filter_size is None:
     if output_size is None:
-            raise ValueError("output_size must be set when filter_size is None")
-        if isinstance(output_size, int):
+        output_size = []
+    elif isinstance(output_size, (list, tuple)):
+        if utils._contain_var(output_size):
+            output_size = utils._convert_to_tensor_list(output_size)
+        else:
+            output_size = utils.convert_to_list(output_size, 2, 'output_size')
+    elif isinstance(output_size, int):
+        output_size = utils.convert_to_list(output_size, 2, 'output_size')
+    elif isinstance(output_size, Variable):
+        check_dtype(output_size.dtype, 'output_size', ['int32', 'int64'],
+                    'conv2d_transpose')
+        if len(output_size.shape) == 1 and (output_size.shape[0] == 1
+                                            or output_size.shape[0] == 2):
+            if output_size.shape[0] == 1:
                 output_size = [output_size, output_size]
+        else:
+            raise ValueError("output_size must contain one or two integers.")
+    else:
+        raise ValueError(
+            "output_size should be int, list[int] or tuple[int] or Tensor")
+
+    if filter_size is None:
+        if output_size is []:
+            raise ValueError("output_size must be set when filter_size is None")
+        if not _non_static_mode():
+            if isinstance(output_size,
+                          Variable) or utils._contain_var(output_size):
+                raise ValueError(
+                    "filter_size should not be None when output_size is Variable or contain Variable in static mode."
+                )
+        else:
+            output_size = utils.convert_shape_to_list(output_size)
+            if len(output_size) == 1:
+                output_size = utils.convert_to_list(output_size[0], 2,
+                                                    'output_size')
 
         h_in = input.shape[2] if data_format == 'NCHW' else input.shape[1]
         w_in = input.shape[3] if data_format == 'NCHW' else input.shape[2]
@@ -4237,13 +4268,6 @@ def conv2d_transpose(input,
     if len(padding) == 4 and utils._is_symmetric_padding(padding, 2):
         padding = [padding[0], padding[2]]
 
-    if output_size is None:
-        output_size = []
-    elif isinstance(output_size, (list, tuple, int)):
-        output_size = utils.convert_to_list(output_size, 2, 'output_size')
-    else:
-        raise ValueError("output_size should be int, list[int] or tuple[int]")
-
     if groups is None:
         groups = 1
     elif groups <= 0:

python/paddle/fluid/tests/unittests/test_conv2d_transpose_op.py

@@ -14,6 +14,7 @@
 
 from __future__ import print_function
 
+import os
 import unittest
 import numpy as np
 
@@ -23,7 +24,9 @@ import paddle.nn as nn
 paddle.enable_static()
 import paddle.fluid.core as core
 import paddle.fluid as fluid
-from paddle.fluid.tests.unittests.op_test import OpTest
+from paddle.fluid import Program, program_guard
+from test_attribute_var import UnittestBase
+from op_test import OpTest
 
 
 def conv2dtranspose_forward_naive(input_, filter_, attrs):
@@ -974,5 +977,175 @@ class TestConv2DTransposeRepr(unittest.TestCase):
         paddle.enable_static()
 
 
+class TestTensorOutputSize1(UnittestBase):
+
+    def init_info(self):
+        self.shapes = [[2, 3, 8, 8]]
+        self.save_path = os.path.join(self.temp_dir.name, self.path_prefix())
+
+    def path_prefix(self):
+        return 'conv2d_transpose_tensor_output_size1'
+
+    def var_prefix(self):
+        return "Vars["
+
+    def call_func(self, x):
+        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
+        output_size = paddle.assign([17])
+        out = paddle.paddle.nn.functional.conv2d_transpose(
+            x, w_var, stride=2, output_size=output_size)
+        return out
+
+    def test_static(self):
+        main_prog = Program()
+        starup_prog = Program()
+        with program_guard(main_prog, starup_prog):
+            fc = paddle.nn.Linear(8, 8)
+            x = paddle.randn([2, 3, 8, 8])
+            x.stop_gradient = False
+            feat = fc(x)
+            out = self.call_func(feat)
+
+            sgd = paddle.optimizer.SGD()
+            sgd.minimize(paddle.mean(out))
+            self.assertTrue(self.var_prefix() in str(main_prog))
+
+            exe = paddle.static.Executor()
+            exe.run(starup_prog)
+            res = exe.run(fetch_list=[feat, out])
+            np.testing.assert_allclose(res[1].shape, (2, 6, 17, 17))
+
+            paddle.static.save_inference_model(self.save_path, [x], [feat, out],
+                                               exe)
+            # Test for Inference Predictor
+            infer_outs = self.infer_prog()
+            np.testing.assert_allclose(infer_outs[1].shape, (2, 6, 17, 17))
+
+
+class TestTensorOutputSize2(TestTensorOutputSize1):
+
+    def path_prefix(self):
+        return 'conv2d_transpose_tensor_output_size2'
+
+    def call_func(self, x):
+        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
+        output_size = [17, paddle.assign([17])]
+        out = paddle.paddle.nn.functional.conv2d_transpose(
+            x, w_var, stride=2, output_size=output_size)
+        return out
+
+
+class TestTensorOutputSize3(TestTensorOutputSize1):
+
+    def path_prefix(self):
+        return 'conv2d_transpose_tensor_output_size3'
+
+    def call_func(self, x):
+        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
+        output_size = paddle.assign([17])
+        out = paddle.fluid.layers.conv2d_transpose(x,
+                                                   num_filters=6,
+                                                   output_size=output_size,
+                                                   filter_size=3,
+                                                   stride=2)
+        return out
+
+
+class TestTensorOutputSize4(TestTensorOutputSize1):
+
+    def path_prefix(self):
+        return 'conv2d_transpose_tensor_output_size4'
+
+    def call_func(self, x):
+        output_size = [17, paddle.assign([17])]
+        out = paddle.fluid.layers.conv2d_transpose(x,
+                                                   num_filters=6,
+                                                   output_size=output_size,
+                                                   filter_size=3,
+                                                   stride=2)
+        return out
+
+
+class TestTensorOutputSize5(TestTensorOutputSize1):
+
+    def path_prefix(self):
+        return 'conv2d_transpose_tensor_output_size5'
+
+    def call_func(self, x):
+        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
+        output_size = [17, paddle.assign([17])]
+        conv2d_trans = paddle.fluid.dygraph.Conv2DTranspose(
+            num_channels=3,
+            num_filters=6,
+            filter_size=3,
+            output_size=output_size,
+            stride=2)
+        out = conv2d_trans(x)
+        return out
+
+
+class TestTensorOutputSize6(TestTensorOutputSize1):
+
+    def path_prefix(self):
+        return 'conv2d_transpose_tensor_output_size6'
+
+    def var_prefix(self):
+        return "Var["
+
+    def call_func(self, x):
+        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
+        output_size = paddle.assign([17, 17])
+        conv2d_trans = paddle.fluid.dygraph.Conv2DTranspose(
+            num_channels=3,
+            num_filters=6,
+            filter_size=3,
+            output_size=output_size,
+            stride=2)
+        out = conv2d_trans(x)
+        return out
+
+
+class TestTensorOutputSize7(TestTensorOutputSize1):
+
+    def path_prefix(self):
+        return 'conv2d_transpose_tensor_output_size7'
+
+    def var_prefix(self):
+        return ""
+
+    def call_func(self, x):
+        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
+        output_size = 17
+        conv2d_trans = paddle.fluid.dygraph.Conv2DTranspose(
+            num_channels=3,
+            num_filters=6,
+            filter_size=3,
+            output_size=output_size,
+            stride=2)
+        out = conv2d_trans(x)
+        return out
+
+
+class TestTensorOutputSize8(TestTensorOutputSize1):
+
+    def path_prefix(self):
+        return 'conv2d_transpose_tensor_output_size8'
+
+    def var_prefix(self):
+        return ""
+
+    def call_func(self, x):
+        w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
+        output_size = [17, 17]
+        conv2d_trans = paddle.fluid.dygraph.Conv2DTranspose(
+            num_channels=3,
+            num_filters=6,
+            filter_size=3,
+            output_size=output_size,
+            stride=2)
+        out = conv2d_trans(x)
+        return out
+
+
 if __name__ == '__main__':
     unittest.main()

python/paddle/nn/functional/conv.py

@@ -17,8 +17,8 @@ import numpy as np
 from ...device import get_cudnn_version
 from ...static import Variable
 from ...fluid import dygraph_utils
-from ...fluid.layers.utils import convert_to_list, _is_symmetric_padding
-from ...fluid.data_feeder import check_variable_and_dtype
+from ...fluid.layers.utils import convert_to_list, _is_symmetric_padding, _contain_var, _convert_to_tensor_list
+from ...fluid.data_feeder import check_variable_and_dtype, check_dtype
 from ...framework import ParamAttr
 from ...fluid.layer_helper import LayerHelper
 from ...tensor.manipulation import unsqueeze, squeeze
@@ -35,6 +35,7 @@ from paddle.device import is_compiled_with_rocm
 from paddle.fluid.framework import _global_flags
 from paddle.fluid.framework import _in_legacy_dygraph
 from paddle.fluid.framework import in_dygraph_mode
+from paddle.fluid.framework import _non_static_mode
 
 __all__ = []
 
@@ -1133,11 +1134,27 @@ def conv2d_transpose(x,
         if output_padding != 0:
             raise ValueError('output_padding option is mutually exclusive with '
                              'output_size')
-        if isinstance(output_size, (list, tuple, int)):
+        if isinstance(output_size, (list, tuple)):
+            if _contain_var(output_size):
+                output_size = _convert_to_tensor_list(output_size)
+            else:
                 output_size = convert_to_list(output_size, 2, 'output_size')
+        elif isinstance(output_size, int):
+            output_size = convert_to_list(output_size, 2, 'output_size')
+        elif isinstance(output_size, Variable):
+            check_dtype(output_size.dtype, 'output_size', ['int32', 'int64'],
+                        'conv2d_transpose')
+            if len(output_size.shape) == 1 and (output_size.shape[0] == 1
+                                                or output_size.shape[0] == 2):
+                if output_size.shape[0] == 1:
+                    output_size = [output_size, output_size]
             else:
                 raise ValueError(
-                "output_size should be int, or list, tuple of ints")
+                    "output_size must contain one or two integers.")
+        else:
+            raise ValueError(
+                "output_size should be int or Tensor or list, tuple of ints or Tensor"
+            )
 
     if output_padding == 0:
         output_padding = []