[Accuracy diff No.80、150] Fix accuracy diff for cumulative_trapezoid, trapezoid API (#73317)

Author: ooooo-create

paddle/phi/kernels/funcs/gather.h

@@ -265,12 +265,14 @@ void GatherV2GradFunction(const phi::CPUContext& ctx,
  for (int64_t i = 0; i < inner_dim_size; i++) {
  for (int64_t j = 0; j < input_index_dim_size; j++) {
  const int64_t index_data_j =
- (index_data[j] < 0 ? index_data[j] + input_index_dim_size
+ (index_data[j] < 0 ? index_data[j] + out_index_dim_size
  : index_data[j]);
  for (int64_t k = 0; k < outer_dim_size; k++) {
  int64_t index = k + index_data_j * outer_dim_size +
  i * outer_dim_size * out_index_dim_size;
- out_data[index] += input_data[j * outer_dim_size + k];
+ out_data[index] +=
+ input_data[i * input_index_dim_size * outer_dim_size +
+ j * outer_dim_size + k];
  }
  }
  }

test/legacy_test/test_gather_op.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
 import unittest
 
 import numpy as np
@@ -908,6 +909,45 @@ def test_pir_out_type(self):
  self.assertTrue(out.dtype == core.DataType.INT64)
 
 
+class TestGatherBackward(unittest.TestCase):
+ def setUp(self):
+ self.shape = [10, 20]
+ self.dtype = 'float32'
+ self.index = (1, 3, 5)
+ self.index_dtype = 'int64'
+ self.places = []
+ if (
+ os.environ.get('FLAGS_CI_both_cpu_and_gpu', 'False').lower()
+ in ['1', 'true', 'on']
+ or not paddle.is_compiled_with_cuda()
+ ):
+ self.places.append(paddle.CPUPlace())
+ if paddle.is_compiled_with_cuda():
+ self.places.append(paddle.CUDAPlace(0))
+
+ def test_gather_backward(self):
+ if len(self.places) != 2:
+ return
+ res_list = []
+ x_np = np.random.random(self.shape).astype(self.dtype)
+ index_np = np.array(self.index, dtype=self.index_dtype)
+ grad_out_np = np.random.random(self.shape).astype(self.dtype)
+ for place in self.places:
+ with base.dygraph.guard(place):
+ x = paddle.to_tensor(x_np, dtype=self.dtype)
+ x.stop_gradient = False
+ index = paddle.to_tensor(index_np, dtype=self.index_dtype)
+ out = paddle.gather(x, index, -1)
+ grad_out = paddle.to_tensor(grad_out_np, dtype=self.dtype)
+ (re,) = paddle.grad(
+ outputs=out,
+ inputs=x,
+ grad_outputs=grad_out,
+ )
+ res_list.append(re.numpy())
+ np.testing.assert_allclose(res_list[0], res_list[1])
+
+
 if __name__ == "__main__":
  paddle.enable_static()
  unittest.main()