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This commit is contained in:
zong_shuai 2021-08-30 10:51:56 +08:00
parent 63faa9c004
commit ccdc9f0164
2 changed files with 15 additions and 15 deletions
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22
tests/st/ops/gpu/test_batchtospace_op.py
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@ -23,9 +23,9 @@ from mindspore.common.initializer import initializer
from mindspore.common.parameter import Parameter from mindspore.common.parameter import Parameter
class BatchToSpaceNet(nn.Cell): class BatchToSpaceNet(nn.Cell):
def __init__(self, nptype, block_size=2, input_shape=(4,1,2,2)): def __init__(self, nptype, block_size=2, input_shape=(4, 1, 2, 2)):
super(BatchToSpaceNet, self).__init__() super(BatchToSpaceNet, self).__init__()
self.BatchToSpace = P.BatchToSpace(block_size=block_size, crops=[[0,0],[0,0]]) self.BatchToSpace = P.BatchToSpace(block_size=block_size, crops=[[0, 0], [0, 0]])
input_size = 1 input_size = 1
for i in input_shape: for i in input_shape:
input_size = input_size*i input_size = input_size*i
@ -39,14 +39,14 @@ class BatchToSpaceNet(nn.Cell):
return y1 return y1
def BatchToSpace(nptype, block_size=2, input_shape=(4,1,2,2)): def BatchToSpace(nptype, block_size=2, input_shape=(4, 1, 2, 2)):
context.set_context(mode=context.GRAPH_MODE, device_target='GPU') context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
input_size = 1 input_size = 1
for i in input_shape: for i in input_shape:
input_size = input_size*i input_size = input_size*i
expect = np.array([[[[0, 4, 1, 5], expect = np.array([[[[0, 4, 1, 5],
[8, 12, 9, 13], [8, 12, 9, 13],
[2, 6, 3, 7], [2, 6, 3, 7],
[10, 14, 11, 15]]]]).astype(nptype) [10, 14, 11, 15]]]]).astype(nptype)
dts = BatchToSpaceNet(nptype, block_size, input_shape) dts = BatchToSpaceNet(nptype, block_size, input_shape)
@ -54,17 +54,17 @@ def BatchToSpace(nptype, block_size=2, input_shape=(4,1,2,2)):
assert (output.asnumpy() == expect).all() assert (output.asnumpy() == expect).all()
def BatchToSpace_pynative(nptype, block_size=2, input_shape=(4,1,2,2)): def BatchToSpace_pynative(nptype, block_size=2, input_shape=(4, 1, 2, 2)):
context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU') context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
input_size = 1 input_size = 1
for i in input_shape: for i in input_shape:
input_size = input_size*i input_size = input_size*i
expect = np.array([[[[0, 4, 1, 5], expect = np.array([[[[0, 4, 1, 5],
[8, 12, 9, 13], [8, 12, 9, 13],
[2, 6, 3, 7], [2, 6, 3, 7],
[10, 14, 11, 15]]]]).astype(nptype) [10, 14, 11, 15]]]]).astype(nptype)
dts = P.BatchToSpace(block_size=block_size, crops=[[0,0],[0,0]]) dts = P.BatchToSpace(block_size=block_size, crops=[[0, 0], [0, 0]])
arr_input = Tensor(np.arange(input_size).reshape(input_shape).astype(nptype)) arr_input = Tensor(np.arange(input_size).reshape(input_shape).astype(nptype))
output = dts(arr_input) output = dts(arr_input)

4
tests/st/ops/gpu/test_spacetobatch_op.py
View File

@ -25,7 +25,7 @@ from mindspore.common.parameter import Parameter
class SpaceToBatchNet(nn.Cell): class SpaceToBatchNet(nn.Cell):
def __init__(self, nptype, block_size=2, input_shape=(1, 1, 4, 4)): def __init__(self, nptype, block_size=2, input_shape=(1, 1, 4, 4)):
super(SpaceToBatchNet, self).__init__() super(SpaceToBatchNet, self).__init__()
self.SpaceToBatch = P.SpaceToBatch(block_size=block_size, paddings=[[0,0],[0,0]]) self.SpaceToBatch = P.SpaceToBatch(block_size=block_size, paddings=[[0, 0], [0, 0]])
input_size = 1 input_size = 1
for i in input_shape: for i in input_shape:
input_size = input_size*i input_size = input_size*i
@ -72,7 +72,7 @@ def SpaceToBatch_pynative(nptype, block_size=2, input_shape=(1, 1, 4, 4)):
[[[5, 7], [[[5, 7],
[13, 15]]]]).astype(nptype) [13, 15]]]]).astype(nptype)
dts = P.SpaceToBatch(block_size=block_size, paddings=[[0,0],[0,0]]) dts = P.SpaceToBatch(block_size=block_size, paddings=[[0, 0], [0, 0]])
arr_input = Tensor(np.arange(input_size).reshape(input_shape).astype(nptype)) arr_input = Tensor(np.arange(input_size).reshape(input_shape).astype(nptype))
output = dts(arr_input) output = dts(arr_input)