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!5754 adding int32 support for Greater gpu kernel 

Merge pull request !5754 from Peilin/add-type-support-for-greater
This commit is contained in:
mindspore-ci-bot 2020-09-09 22:29:12 +08:00 committed by Gitee
parent cbeb2dbf5c f020e19636
commit 87d0d0bf8d
2 changed files with 12 additions and 0 deletions
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3
mindspore/ccsrc/backend/kernel_compiler/gpu/math/broadcast_gpu_kernel.cc
View File

@ -109,6 +109,9 @@ MS_REG_GPU_KERNEL_ONE(
BroadcastOpGpuKernel, half)
// int32
MS_REG_GPU_KERNEL_ONE(
Greater, KernelAttr().AddInputAttr(kNumberTypeInt32).AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeBool),
BroadcastOpGpuKernel, int)
MS_REG_GPU_KERNEL_ONE(
Less, KernelAttr().AddInputAttr(kNumberTypeInt32).AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeBool),
BroadcastOpGpuKernel, int)

9
tests/st/ops/gpu/test_broadcast_op.py
View File

@ -43,6 +43,9 @@ def test_nobroadcast():
output_ms = P.Greater()(Tensor(x1_np), Tensor(x2_np))
output_np = x1_np > x2_np
assert np.allclose(output_ms.asnumpy(), output_np)
output_ms = P.Greater()(Tensor(x1_np_int32), Tensor(x2_np_int32))
output_np = x1_np_int32 > x2_np_int32
assert np.allclose(output_ms.asnumpy(), output_np)
output_ms = P.Less()(Tensor(x1_np), Tensor(x2_np))
output_np = x1_np < x2_np
@ -132,6 +135,9 @@ def test_broadcast():
output_ms = P.Greater()(Tensor(x1_np), Tensor(x2_np))
output_np = x1_np > x2_np
assert np.allclose(output_ms.asnumpy(), output_np)
output_ms = P.Greater()(Tensor(x1_np_int32), Tensor(x2_np_int32))
output_np = x1_np_int32 > x2_np_int32
assert np.allclose(output_ms.asnumpy(), output_np)
output_ms = P.Less()(Tensor(x1_np), Tensor(x2_np))
output_np = x1_np < x2_np
@ -175,6 +181,9 @@ def test_broadcast_diff_dims():
output_ms = P.Maximum()(Tensor(x1_np), Tensor(x2_np))
output_np = np.maximum(x1_np, x2_np)
assert np.allclose(output_ms.asnumpy(), output_np)
output_ms = P.Greater()(Tensor(x1_np_int32), Tensor(x2_np_int32))
output_np = x1_np_int32 > x2_np_int32
assert np.allclose(output_ms.asnumpy(), output_np)
output_ms = P.Greater()(Tensor(x1_np), Tensor(x2_np))
output_np = x1_np > x2_np