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未验证 提交 dfa893fd 编写于 作者: 傅 傅剑寒 提交者： GitHub
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[AMP&OP_TEST] Fix interp test case (#52282) 

* delete check_dygraph and use default atol,max_relative_error

* add test case for bicubic_interp
上级 7788b65e
隐藏空白更改
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Showing with 53 addition and 93 deletion
python/paddle/fluid/tests/unittests/test_bicubic_interp_v2_op.py
浏览文件 @ dfa893fd
......@@ -104,15 +104,17 @@ def bicubic_interp_test(
align_corners=True,
align_mode=0,
):
if isinstance(scale, (float, int)):
if isinstance(scale, float) or isinstance(scale, int):
scale_list = []
for _ in range(len(x.shape) - 2):
scale_list.append(scale)
scale = list(map(float, scale_list))
elif isinstance(scale, (list, tuple)):
elif isinstance(scale, list) or isinstance(scale, tuple):
scale = list(map(float, scale))
if SizeTensor is not None:
if not isinstance(SizeTensor, (list, tuple)):
if not isinstance(SizeTensor, list) and not isinstance(
SizeTensor, tuple
):
SizeTensor = [SizeTensor]
return paddle._C_ops.bicubic_interp(
x,
......@@ -264,7 +266,7 @@ class TestBicubicInterpOp(OpTest):
in_w = self.input_shape[2]
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0.0:
scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -303,7 +305,7 @@ class TestBicubicInterpOp(OpTest):
'data_layout': self.data_layout,
}
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0.0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -374,15 +376,10 @@ class TestBicubicInterpCase1FP16(TestBicubicInterpOpFP16):
self.dtype = np.float16
# this case will cause accuracy loss （backward:0.008773442)
# class TestBicubicInterpCase2FP16(TestBicubicInterpOpFP16):
# def init_test_case(self):
# self.interp_method = 'bicubic'
# self.input_shape = [3, 3, 9, 6]
# self.out_h = 10
# self.out_w = 8
# self.scale = []
# self.align_corners = True
class TestBicubicInterpCase2FP16(TestBicubicInterpOpFP16):
def init_test_case(self):
create_test_case2(self)
self.dtype = np.float16
class TestBicubicInterpCase3FP16(TestBicubicInterpOpFP16):
......@@ -424,7 +421,6 @@ class TestBicubicInterpOpBF16(OpTest):
self.op_type = "bicubic_interp_v2"
# NOTE(dev): some AsDispensible input is not used under imperative mode.
# Skip check_dygraph while found them in Inputs.
self.check_dygraph = True
self.dtype = np.uint16
input_np = np.random.random(self.input_shape).astype("float32")
scale_h = 0
......@@ -465,10 +461,8 @@ class TestBicubicInterpOpBF16(OpTest):
self.inputs = {'X': convert_float_to_uint16(input_np)}
if self.out_size is not None:
self.inputs['OutSize'] = self.out_size
self.check_dygraph = False
if self.actual_shape is not None:
self.inputs['OutSize'] = self.actual_shape
self.check_dygraph = False
self.attrs = {
'out_h': self.out_h,
......@@ -487,16 +481,10 @@ class TestBicubicInterpOpBF16(OpTest):
self.outputs = {'Out': convert_float_to_uint16(output_np)}
def test_check_output(self):
self.check_output(check_dygraph=self.check_dygraph, atol=1e-2)
self.check_output()
def test_check_grad(self):
self.check_grad(
['X'],
'Out',
in_place=True,
check_dygraph=self.check_dygraph,
max_relative_error=1e-2,
)
self.check_grad(['X'], 'Out', in_place=True)
def init_test_case(self):
create_test_case0(self)
......
python/paddle/fluid/tests/unittests/test_bilinear_interp_v2_op.py
浏览文件 @ dfa893fd
......@@ -121,12 +121,12 @@ def bilinear_interp_test(
align_corners=True,
align_mode=0,
):
if isinstance(scale, (float, int)):
if isinstance(scale, float) or isinstance(scale, int):
scale_list = []
for _ in range(len(x.shape) - 2):
scale_list.append(scale)
scale = list(map(float, scale_list))
elif isinstance(scale, (list, tuple)):
elif isinstance(scale, list) or isinstance(scale, tuple):
scale = list(map(float, scale))
if SizeTensor is not None:
if not isinstance(SizeTensor, list) and not isinstance(
......@@ -254,7 +254,7 @@ class TestBilinearInterpOp(OpTest):
scale_h = 0
scale_w = 0
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0.0:
scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -295,7 +295,7 @@ class TestBilinearInterpOp(OpTest):
'data_layout': self.data_layout,
}
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0.0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -604,7 +604,7 @@ class TestBilinearInterpOpUint8(OpTest):
).astype("uint8")
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -641,7 +641,7 @@ class TestBilinearInterpOpUint8(OpTest):
'align_mode': self.align_mode,
}
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -778,7 +778,7 @@ class TestBilinearInterpOp_attr_tensor(OpTest):
if self.scale_by_1Dtensor:
self.inputs['Scale'] = np.array([self.scale]).astype("float32")
elif self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -805,7 +805,7 @@ class TestBilinearInterpOp_attr_tensor(OpTest):
self.attrs['out_h'] = self.out_h
self.attrs['out_w'] = self.out_w
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......
python/paddle/fluid/tests/unittests/test_linear_interp_v2_op.py
浏览文件 @ dfa893fd
......@@ -52,12 +52,12 @@ def linear_interp_test(
align_corners=True,
align_mode=0,
):
if isinstance(scale, (float, int)):
if isinstance(scale, float) or isinstance(scale, int):
scale_list = []
for _ in range(len(x.shape) - 2):
scale_list.append(scale)
scale = list(map(float, scale_list))
elif isinstance(scale, (list, tuple)):
elif isinstance(scale, list) or isinstance(scale, tuple):
scale = list(map(float, scale))
if SizeTensor is not None:
if not isinstance(SizeTensor, list) and not isinstance(
......@@ -153,7 +153,7 @@ class TestLinearInterpOp(OpTest):
in_w = self.input_shape[1]
if self.scale > 0:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
self.scale = float(self.scale)
if isinstance(self.scale, list):
self.scale = float(self.scale[0])
......@@ -185,7 +185,7 @@ class TestLinearInterpOp(OpTest):
'data_layout': self.data_layout,
}
if self.scale > 0:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
self.scale = [float(self.scale)]
self.attrs['scale'] = self.scale
self.outputs = {'Out': output_np}
......@@ -267,7 +267,7 @@ class TestLinearInterpOpSizeTensor(TestLinearInterpOp):
in_w = self.input_shape[1]
if self.scale > 0:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
self.scale = float(self.scale)
if isinstance(self.scale, list):
self.scale = float(self.scale[0])
......@@ -307,7 +307,7 @@ class TestLinearInterpOpSizeTensor(TestLinearInterpOp):
'data_layout': self.data_layout,
}
if self.scale > 0:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
self.scale = [self.scale[0], self.scale[0]]
......@@ -439,7 +439,7 @@ class TestResizeLinearOpUint8(OpTest):
input_np = np.random.random(self.input_shape).astype("uint8")
if self.scale > 0:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
self.scale = float(self.scale)
if isinstance(self.scale, list):
self.scale = float(self.scale[0])
......@@ -467,7 +467,7 @@ class TestResizeLinearOpUint8(OpTest):
'align_mode': self.align_mode,
}
if self.scale > 0:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
self.scale = [self.scale[0], self.scale[0]]
......
python/paddle/fluid/tests/unittests/test_nearest_interp_v2_op.py
浏览文件 @ dfa893fd
......@@ -107,12 +107,12 @@ def nearest_interp_test(
align_corners=True,
align_mode=0,
):
if isinstance(scale, (float, int)):
if isinstance(scale, float) or isinstance(scale, int):
scale_list = []
for _ in range(len(x.shape) - 2):
scale_list.append(scale)
scale = list(map(float, scale_list))
elif isinstance(scale, (list, tuple)):
elif isinstance(scale, list) or isinstance(scale, tuple):
scale = list(map(float, scale))
if SizeTensor is not None:
if not isinstance(SizeTensor, list) and not isinstance(
......@@ -302,7 +302,7 @@ class TestNearestInterpOp(OpTest):
scale_h = 0
scale_w = 0
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
scale_d = scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -374,7 +374,7 @@ class TestNearestInterpOp(OpTest):
'data_layout': self.data_layout,
}
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -445,16 +445,10 @@ class TestNearestNeighborInterpActualShape(TestNearestInterpOp):
class TestNearestInterpOpFP16(TestNearestInterpOp):
def test_check_output(self):
self.check_output(check_dygraph=True, atol=1e-3)
self.check_output()
def test_check_grad(self):
self.check_grad(
['X'],
'Out',
in_place=True,
check_dygraph=True,
max_relative_error=1e-2,
)
self.check_grad(['X'], 'Out', in_place=True)
def init_test_case(self):
create_test_case0(self)
......@@ -615,16 +609,10 @@ class TestNearestInterpOpBF16(OpTest):
self.outputs = {'Out': convert_float_to_uint16(output_np)}
def test_check_output(self):
self.check_output(check_dygraph=True, atol=1e-2)
self.check_output()
def test_check_grad(self):
self.check_grad(
['X'],
'Out',
in_place=True,
check_dygraph=True,
max_relative_error=1e-2,
)
self.check_grad(['X'], 'Out', in_place=True)
def init_test_case(self):
create_test_case0(self)
......@@ -709,7 +697,7 @@ class TestNearestInterpOpUint8(OpTest):
).astype("uint8")
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -743,7 +731,7 @@ class TestNearestInterpOpUint8(OpTest):
'align_corners': self.align_corners,
}
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -854,7 +842,7 @@ class TestNearestInterpOp_attr_tensor(OpTest):
if self.scale_by_1Dtensor:
self.inputs['Scale'] = np.array([self.scale]).astype("float64")
elif self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -881,7 +869,7 @@ class TestNearestInterpOp_attr_tensor(OpTest):
self.attrs['out_h'] = self.out_h
self.attrs['out_w'] = self.out_w
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......
python/paddle/fluid/tests/unittests/test_trilinear_interp_v2_op.py
浏览文件 @ dfa893fd
......@@ -120,12 +120,12 @@ def trilinear_interp_test(
align_corners=True,
align_mode=0,
):
if isinstance(scale, (float, int)):
if isinstance(scale, float) or isinstance(scale, int):
scale_list = []
for _ in range(len(x.shape) - 2):
scale_list.append(scale)
scale = list(map(float, scale_list))
elif isinstance(scale, (list, tuple)):
elif isinstance(scale, list) or isinstance(scale, tuple):
scale = list(map(float, scale))
if SizeTensor is not None:
if not isinstance(SizeTensor, list) and not isinstance(
......@@ -287,7 +287,6 @@ class TestTrilinearInterpOp(OpTest):
self.op_type = "trilinear_interp_v2"
# NOTE(dev): some AsDispensible input is not used under imperative mode.
# Skip check_dygraph while found them in Inputs.
self.check_dygraph = True
input_np = np.random.random(self.input_shape).astype(self.dtype)
scale_w = 0
......@@ -303,7 +302,7 @@ class TestTrilinearInterpOp(OpTest):
in_w = self.input_shape[3]
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
scale_d = scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -354,7 +353,7 @@ class TestTrilinearInterpOp(OpTest):
'data_layout': data_layout,
}
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -455,16 +454,10 @@ class TestTrilinearInterpDatalayout(TestTrilinearInterpOp):
class TestTrilinearInterpOpFP16(TestTrilinearInterpOp):
def test_check_output(self):
self.check_output(check_dygraph=self.check_dygraph, atol=1e-3)
self.check_output()
def test_check_grad(self):
self.check_grad(
['X'],
'Out',
in_place=True,
check_dygraph=self.check_dygraph,
max_relative_error=1e-2,
)
self.check_grad(['X'], 'Out', in_place=True)
def init_test_case(self):
create_test_case0(self)
......@@ -522,7 +515,6 @@ class TestNearestInterpOpBF16(OpTest):
self.op_type = "trilinear_interp_v2"
# NOTE(dev): some AsDispensible input is not used under imperative mode.
# Skip check_dygraph while found them in Inputs.
self.check_dygraph = True
self.dtype = np.uint16
input_np = np.random.random(self.input_shape).astype("float32")
......@@ -573,10 +565,8 @@ class TestNearestInterpOpBF16(OpTest):
self.inputs = {'X': convert_float_to_uint16(input_np)}
if self.out_size is not None:
self.inputs['OutSize'] = self.out_size
self.check_dygraph = False
if self.actual_shape is not None:
self.inputs['OutSize'] = self.actual_shape
self.check_dygraph = False
# c++ end treat NCDHW the same way as NCHW
if self.data_layout == 'NCDHW':
data_layout = 'NCHW'
......@@ -601,16 +591,10 @@ class TestNearestInterpOpBF16(OpTest):
self.outputs = {'Out': convert_float_to_uint16(output_np)}
def test_check_output(self):
self.check_output(check_dygraph=self.check_dygraph, atol=1e-2)
self.check_output()
def test_check_grad(self):
self.check_grad(
['X'],
'Out',
in_place=True,
check_dygraph=self.check_dygraph,
max_relative_error=1e-2,
)
self.check_grad(['X'], 'Out', in_place=True)
def init_test_case(self):
create_test_case0(self)
......@@ -688,7 +672,7 @@ class TestTrilinearInterpOpUint8(OpTest):
).astype("uint8")
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
scale_d = scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -731,7 +715,7 @@ class TestTrilinearInterpOpUint8(OpTest):
'align_mode': self.align_mode,
}
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -865,7 +849,7 @@ class TestTrilinearInterpOp_attr_tensor(OpTest):
if self.scale_by_1Dtensor:
self.inputs['Scale'] = np.array([self.scale]).astype("float32")
elif self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
scale_d = scale_h = scale_w = float(self.scale)
if isinstance(self.scale, list) and len(self.scale) == 1:
......@@ -896,7 +880,7 @@ class TestTrilinearInterpOp_attr_tensor(OpTest):
self.attrs['out_h'] = self.out_h
self.attrs['out_w'] = self.out_w
if self.scale:
if isinstance(self.scale, (float, int)):
if isinstance(self.scale, float) or isinstance(self.scale, int):
if self.scale > 0:
self.scale = [self.scale]
if isinstance(self.scale, list) and len(self.scale) == 1:
......
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