【Hackathon 6th No.26】为 paddle.view 进行功能增强

paddle/phi/kernels/stride/view_kernel.cc

@@ -23,7 +23,32 @@ void ViewShapeKernel(const Context& dev_ctx,
                      const DenseTensor& input,
                      const std::vector<int64_t>& dims,
                      DenseTensor* out) {
-  DDim new_dims = DDim(dims.data(), static_cast<int>(dims.size()));
+  // infer dims
+  auto infer_dim = -1;
+  auto new_size = 1;
+  auto numel = input.numel();
+  std::vector<int64_t> dims_copy = dims;
+  for (int dim = 0, ndim = dims_copy.size(); dim < ndim; ++dim) {
+    if (dims_copy[dim] == -1) {
+      if (infer_dim >= 0) {
+        PADDLE_THROW(phi::errors::Fatal("Only one dimension can be inferred"));
+      }
+      infer_dim = dim;
+    } else if (dims_copy[dim] >= 0) {
+      new_size *= dims_copy[dim];
+    } else {
+      PADDLE_THROW(phi::errors::OutOfRange("Tensor idx is out of range"));
+    }
+  }
+  PADDLE_ENFORCE_NE(new_size,
+                    0,
+                    phi::errors::Unavailable(
+                        "cannot reshape tensor of 0 elements into shape "));
+  if (infer_dim >= 0 && new_size > 0 && numel % new_size == 0) {
+    dims_copy[infer_dim] = numel / new_size;
+  }
+
+  DDim new_dims = DDim(dims_copy.data(), static_cast<int>(dims_copy.size()));
   DDim stride;
   if (ReshapeStride(input.dims(), input.strides(), new_dims, stride)) {
     auto meta = input.meta();

python/paddle/tensor/manipulation.py

@@ -6401,6 +6401,24 @@ def view(x, shape_or_dtype, name=None):
             >>> print(out.shape)
             [2, 4, 24]
 
+            >>> import paddle
+            >>> paddle.base.set_flags({"FLAGS_use_stride_kernel": True})
+
+            >>> x = paddle.rand([2, 4, 6], dtype="float32")
+
+            >>> out = paddle.view(x, [8, -1])
+            >>> print(out.shape)
+            [8, 6]
+
+            >>> import paddle
+            >>> paddle.base.set_flags({"FLAGS_use_stride_kernel": True})
+
+            >>> x = paddle.rand([2, 4, 6], dtype="float32")
+
+            >>> out = paddle.view(x, paddle.uint8")
+            >>> print(out.shape)
+            [2, 4, 24]
+
     """
     if isinstance(shape_or_dtype, (list, tuple)):
         return _C_ops.view_shape(x, shape_or_dtype)

test/deprecated/legacy_test/test_stride.py

@@ -556,6 +556,47 @@ def call_view2(self):
 
         self.assertTrue(out_c._is_shared_buffer_with(out))
 
+    def call_view3(self):
+        x_np = np.random.random(size=[10, 10, 10, 20]).astype('float32')
+        x = paddle.to_tensor(x_np)
+        np.testing.assert_allclose(x.numpy(), x_np)
+
+        # shape inference
+        out = paddle.view(x, [10, 100, -1])
+        np_out = x_np.reshape(10, 100, 20)
+
+        np.testing.assert_allclose(out.numpy(), np_out)
+
+        self.assertTrue(out.is_contiguous())
+
+        self.assertTrue(x._is_shared_buffer_with(out))
+
+        out_c = out.contiguous()
+
+        np.testing.assert_allclose(out_c.numpy(), np_out)
+
+        self.assertTrue(out_c._is_shared_buffer_with(out))
+
+    def call_view4(self):
+        x_np = np.random.random(size=[10, 10, 10, 20]).astype('float32')
+        x = paddle.to_tensor(x_np)
+        np.testing.assert_allclose(x.numpy(), x_np)
+
+        out = paddle.view(x, paddle.uint8)
+        np_out = x_np.view(np.uint8)
+
+        np.testing.assert_allclose(out.numpy(), np_out)
+
+        self.assertTrue(out.is_contiguous())
+
+        self.assertTrue(x._is_shared_buffer_with(out))
+
+        out_c = out.contiguous()
+
+        np.testing.assert_allclose(out_c.numpy(), np_out)
+
+        self.assertTrue(out_c._is_shared_buffer_with(out))
+
     def call_view_as(self):
         x_np = np.random.random(size=[10, 10, 10, 20]).astype('float32')
         x = paddle.to_tensor(x_np)
@@ -618,6 +659,8 @@ def call_stride(self):
         self.call_as_strided()
         self.call_view()
         self.call_view2()
+        self.call_view3()
+        self.call_view4()
         self.call_view_as()
         self.call_unfold()