未验证 提交 96d2f337 编写于 作者: T tanzhipeng 提交者: GitHub

modify sequence_conv_xpu op test. test=kunlun (#40347)

上级 7dad9f70
...@@ -21,6 +21,8 @@ import random ...@@ -21,6 +21,8 @@ import random
import sys import sys
sys.path.append("../") sys.path.append("../")
from op_test_xpu import XPUOpTest from op_test_xpu import XPUOpTest
from xpu.get_test_cover_info import create_test_class, get_xpu_op_support_types
from xpu.get_test_cover_info import XPUOpTestWrapper
paddle.enable_static() paddle.enable_static()
np.set_printoptions(threshold=np.inf) np.set_printoptions(threshold=np.inf)
...@@ -73,10 +75,15 @@ def seqconv(x, ...@@ -73,10 +75,15 @@ def seqconv(x,
return np.dot(col, filter) return np.dot(col, filter)
class TestSeqProject(XPUOpTest): class XPUTestSequenceConv(XPUOpTestWrapper):
def __init__(self):
self.op_name = 'sequence_conv'
class TestSeqProject(XPUOpTest):
def setUp(self): def setUp(self):
self.init_test_case() self.init_test_case()
self.op_type = 'sequence_conv' self.op_type = 'sequence_conv'
self.dtype = self.in_type
self.use_xpu = True self.use_xpu = True
if self.context_length == 1 \ if self.context_length == 1 \
...@@ -90,16 +97,17 @@ class TestSeqProject(XPUOpTest): ...@@ -90,16 +97,17 @@ class TestSeqProject(XPUOpTest):
# one level, batch size # one level, batch size
x = np.random.uniform(-6.10907e-05, 0.000104218, x = np.random.uniform(-6.10907e-05, 0.000104218,
[self.input_size[0], [self.input_size[0],
self.input_size[1]]).astype('float32') self.input_size[1]]).astype(self.dtype)
w = np.random.uniform(-3.17068e-05, 0.000159822, [ w = np.random.uniform(-3.17068e-05, 0.000159822, [
self.context_length * self.input_size[1], self.output_represention self.context_length * self.input_size[1],
]).astype('float32') self.output_represention
]).astype(self.dtype)
begin_pad = np.max([0, -self.context_start]) begin_pad = np.max([0, -self.context_start])
end_pad = np.max([0, self.context_start + self.context_length - 1]) end_pad = np.max([0, self.context_start + self.context_length - 1])
total_pad = begin_pad + end_pad total_pad = begin_pad + end_pad
padding_data = np.random.uniform( padding_data = np.random.uniform(
0, 0, [total_pad, self.input_size[1]]).astype('float32') 0, 0, [total_pad, self.input_size[1]]).astype(self.dtype)
self.pad_data = padding_data self.pad_data = padding_data
self.inputs = { self.inputs = {
'X': (x, self.lod), 'X': (x, self.lod),
...@@ -121,8 +129,9 @@ class TestSeqProject(XPUOpTest): ...@@ -121,8 +129,9 @@ class TestSeqProject(XPUOpTest):
'paddingTrainable': self.padding_trainable, 'paddingTrainable': self.padding_trainable,
'contextStride': self.context_stride 'contextStride': self.context_stride
} }
out = seqconv(x, self.lod, w, self.context_length, self.context_start, out = seqconv(x, self.lod, w, self.context_length,
self.padding_trainable, self.pad_data) self.context_start, self.padding_trainable,
self.pad_data)
self.outputs = {'Out': out} self.outputs = {'Out': out}
def test_check_output(self): def test_check_output(self):
...@@ -153,7 +162,8 @@ class TestSeqProject(XPUOpTest): ...@@ -153,7 +162,8 @@ class TestSeqProject(XPUOpTest):
def test_check_grad_padding_filter(self): def test_check_grad_padding_filter(self):
if self.padding_trainable: if self.padding_trainable:
self.check_grad(self.inputs_val_no_x, 'Out', no_grad_set=set(['X'])) self.check_grad(
self.inputs_val_no_x, 'Out', no_grad_set=set(['X']))
def init_test_case(self): def init_test_case(self):
self.input_row = 7 self.input_row = 7
...@@ -171,8 +181,7 @@ class TestSeqProject(XPUOpTest): ...@@ -171,8 +181,7 @@ class TestSeqProject(XPUOpTest):
self.lod[0].append(offset_lod[0][i + 1] - offset_lod[0][i]) self.lod[0].append(offset_lod[0][i + 1] - offset_lod[0][i])
self.output_represention = 8 # output feature size self.output_represention = 8 # output feature size
class TestSeqProjectCase1(TestSeqProject):
class TestSeqProjectCase1(TestSeqProject):
def init_test_case(self): def init_test_case(self):
self.input_row = 11 self.input_row = 11
self.context_start = -2 self.context_start = -2
...@@ -188,8 +197,7 @@ class TestSeqProjectCase1(TestSeqProject): ...@@ -188,8 +197,7 @@ class TestSeqProjectCase1(TestSeqProject):
self.lod[0].append(offset_lod[0][i + 1] - offset_lod[0][i]) self.lod[0].append(offset_lod[0][i + 1] - offset_lod[0][i])
self.output_represention = 8 # output feature size self.output_represention = 8 # output feature size
class TestSeqProjectCase2Len0(TestSeqProject):
class TestSeqProjectCase2Len0(TestSeqProject):
def init_test_case(self): def init_test_case(self):
self.input_row = 11 self.input_row = 11
self.context_start = -2 self.context_start = -2
...@@ -205,8 +213,7 @@ class TestSeqProjectCase2Len0(TestSeqProject): ...@@ -205,8 +213,7 @@ class TestSeqProjectCase2Len0(TestSeqProject):
self.lod[0].append(offset_lod[0][i + 1] - offset_lod[0][i]) self.lod[0].append(offset_lod[0][i + 1] - offset_lod[0][i])
self.output_represention = 8 # output feature size self.output_represention = 8 # output feature size
class TestSeqProjectCase3(TestSeqProject):
class TestSeqProjectCase3(TestSeqProject):
def init_test_case(self): def init_test_case(self):
self.input_row = 25 self.input_row = 25
self.context_start = -2 self.context_start = -2
...@@ -225,8 +232,7 @@ class TestSeqProjectCase3(TestSeqProject): ...@@ -225,8 +232,7 @@ class TestSeqProjectCase3(TestSeqProject):
self.lod[0].append(offset_lod[0][i + 1] - offset_lod[0][i]) self.lod[0].append(offset_lod[0][i + 1] - offset_lod[0][i])
self.output_represention = 8 # output feature size self.output_represention = 8 # output feature size
class TestSeqProjectCase4(TestSeqProject):
class TestSeqProjectCase4(TestSeqProject):
def init_test_case(self): def init_test_case(self):
self.input_row = 7835 self.input_row = 7835
self.input_col = 128 self.input_col = 128
...@@ -237,18 +243,19 @@ class TestSeqProjectCase4(TestSeqProject): ...@@ -237,18 +243,19 @@ class TestSeqProjectCase4(TestSeqProject):
self.input_size = [self.input_row, self.input_col] self.input_size = [self.input_row, self.input_col]
offset_lod = [[ offset_lod = [[
0, 1, 2, 3, 131, 241, 242, 263, 264, 265, 266, 267, 268, 387, 515, 0, 1, 2, 3, 131, 241, 242, 263, 264, 265, 266, 267, 268, 387,
516, 644, 645, 772, 794, 922, 923, 924, 944, 945, 1073, 1074, 1202, 515, 516, 644, 645, 772, 794, 922, 923, 924, 944, 945, 1073,
1330, 1458, 1556, 1557, 1558, 1686, 1748, 1876, 1912, 1913, 1914, 1074, 1202, 1330, 1458, 1556, 1557, 1558, 1686, 1748, 1876,
2032, 2066, 2194, 2308, 2309, 2347, 2475, 2476, 2477, 2478, 2606, 1912, 1913, 1914, 2032, 2066, 2194, 2308, 2309, 2347, 2475,
2607, 2735, 2736, 2737, 2738, 2838, 2966, 2967, 2968, 2969, 3097, 2476, 2477, 2478, 2606, 2607, 2735, 2736, 2737, 2738, 2838,
3225, 3353, 3481, 3482, 3520, 3642, 3643, 3754, 3882, 3883, 4010, 2966, 2967, 2968, 2969, 3097, 3225, 3353, 3481, 3482, 3520,
4011, 4012, 4140, 4219, 4228, 4356, 4357, 4415, 4475, 4476, 4604, 3642, 3643, 3754, 3882, 3883, 4010, 4011, 4012, 4140, 4219,
4605, 4606, 4694, 4695, 4808, 4936, 4961, 4962, 5004, 5132, 5260, 4228, 4356, 4357, 4415, 4475, 4476, 4604, 4605, 4606, 4694,
5312, 5440, 5441, 5569, 5570, 5675, 5676, 5750, 5810, 5811, 5939, 4695, 4808, 4936, 4961, 4962, 5004, 5132, 5260, 5312, 5440,
6021, 6149, 6277, 6278, 6364, 6425, 6519, 6647, 6648, 6739, 6867, 5441, 5569, 5570, 5675, 5676, 5750, 5810, 5811, 5939, 6021,
6995, 6996, 7120, 7223, 7244, 7367, 7407, 7408, 7467, 7595, 7699, 6149, 6277, 6278, 6364, 6425, 6519, 6647, 6648, 6739, 6867,
7827, 7835 6995, 6996, 7120, 7223, 7244, 7367, 7407, 7408, 7467, 7595,
7699, 7827, 7835
]] ]]
self.lod = [[]] self.lod = [[]]
# convert from offset-based lod to length-based lod # convert from offset-based lod to length-based lod
...@@ -257,6 +264,11 @@ class TestSeqProjectCase4(TestSeqProject): ...@@ -257,6 +264,11 @@ class TestSeqProjectCase4(TestSeqProject):
self.output_represention = 8 # output feature size self.output_represention = 8 # output feature size
support_types = get_xpu_op_support_types('sequence_conv')
for stype in support_types:
create_test_class(globals(), XPUTestSequenceConv, stype)
class TestSeqConvApi(unittest.TestCase): class TestSeqConvApi(unittest.TestCase):
def test_api(self): def test_api(self):
import paddle.fluid as fluid import paddle.fluid as fluid
......
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