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Commit 61a7dc0e authored by wooway777's avatar wooway777
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issue/666 - Standardized test imports

parent 406c9668
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Showing with 165 additions and 93 deletions
test/infinicore/ops/max_unpool2d.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
from framework.tensor import TensorInitializer
# Test cases format:
......@@ -28,40 +27,72 @@ _TEST_CASES_DATA = [
# ========== Basic cases ==========
# small sizes with different stride/padding and optional output_size
((1, 1, 16, 16), (2, 2), (2, 2), (0, 0), False, None),
((2, 3, 16, 16), (2, 2), None, None, False, None), # default stride / padding
((2, 3, 8, 8), (3, 3), (2, 2), (1, 1), False, None),
((1, 4, 7, 9), (2, 2), (2, 2), (0, 0), False, None),
((4, 8, 14, 14), (3, 3), (2, 2), (1, 1), True, (27, 27)), # H,W: (14-1)*2 - 2 + 3 = 27
((4, 8, 14, 14), (2, 2), None, (1, 1), True, (26, 26)), # H,W: (14-1)*2 - 2 + 2 = 26
((2, 16, 10, 12), (2, 2), (2, 2), (0, 0), True, (20, 24)), # H: (10-1)*2+2, W: (12-1)*2+2
((2, 16, 10, 12), (3, 3), (2, 2), (1, 1), True, (19, 23)), # H: (10-1)*2-2+3, W: (12-1)*2-2+3
((2, 3, 16, 16), (2, 2), None, None, False, None), # default stride / padding
((2, 3, 8, 8), (3, 3), (2, 2), (1, 1), False, None),
((1, 4, 7, 9), (2, 2), (2, 2), (0, 0), False, None),
(
(4, 8, 14, 14),
(3, 3),
(2, 2),
(1, 1),
True,
(27, 27),
), # H,W: (14-1)*2 - 2 + 3 = 27
(
(4, 8, 14, 14),
(2, 2),
None,
(1, 1),
True,
(26, 26),
), # H,W: (14-1)*2 - 2 + 2 = 26
(
(2, 16, 10, 12),
(2, 2),
(2, 2),
(0, 0),
True,
(20, 24),
), # H: (10-1)*2+2, W: (12-1)*2+2
(
(2, 16, 10, 12),
(3, 3),
(2, 2),
(1, 1),
True,
(19, 23),
), # H: (10-1)*2-2+3, W: (12-1)*2-2+3
# ========== Large-scale performance test cases ==========
# typical CNN activation map sizes and larger inputs
((32, 64, 56, 56), (2, 2), (2, 2), (0, 0), False, None),
((32, 64, 56, 56), (3, 3), (2, 2), (1, 1), False, None),
((64, 128, 28, 28), (2, 2), (2, 2), (0, 0), False, None),
((64, 128, 28, 28), (3, 3), (2, 2), (1, 1), False, None),
((32, 64, 56, 56), (2, 2), (2, 2), (0, 0), False, None),
((32, 64, 56, 56), (3, 3), (2, 2), (1, 1), False, None),
((64, 128, 28, 28), (2, 2), (2, 2), (0, 0), False, None),
((64, 128, 28, 28), (3, 3), (2, 2), (1, 1), False, None),
((128, 256, 14, 14), (2, 2), (2, 2), (0, 0), False, None),
((128, 256, 14, 14), (3, 3), (2, 2), (1, 1), False, None),
((256, 512, 7, 7), (2, 2), (2, 2), (0, 0), False, None),
((256, 512, 7, 7), (3, 3), (2, 2), (1, 1), False, None),
((256, 512, 7, 7), (2, 2), (2, 2), (0, 0), False, None),
((256, 512, 7, 7), (3, 3), (2, 2), (1, 1), False, None),
# large inputs with explicit output_size
((16, 32, 64, 64), (2, 2), (2, 2), (0, 0), True, (128, 128)),
((16, 32, 64, 64), (2, 2), (2, 2), (0, 0), True, (128, 128)),
# H,W: (64-1)*2 - 0 + 2 = 128
((16, 32, 64, 64), (3, 3), (2, 2), (1, 1), True, (127, 127)),
((16, 32, 64, 64), (3, 3), (2, 2), (1, 1), True, (127, 127)),
# H,W: (64-1)*2 - 2 + 3 = 127
((8, 64, 32, 48), (2, 2), (2, 2), (0, 0), True, (64, 96)),
((8, 64, 32, 48), (2, 2), (2, 2), (0, 0), True, (64, 96)),
# H: (32-1)*2+2=64, W: (48-1)*2+2=96
((8, 64, 32, 48), (3, 3), (2, 2), (1, 1), True, (63, 95)),
((8, 64, 32, 48), (3, 3), (2, 2), (1, 1), True, (63, 95)),
# H: (32-1)*2-2+3=63, W: (48-1)*2-2+3=95
# ========== Edge cases ==========
((1, 1, 1, 1), (1, 1), (1, 1), (0, 0), False, None),
((1, 4, 2, 2), (2, 2), (2, 2), (0, 0), True, (4, 4)), # H,W: (2-1)*2+2=4
((1, 4, 2, 2), (2, 2), (2, 2), (0, 0), True, (4, 4)), # H,W: (2-1)*2+2=4
((1, 2, 1, 8), (2, 2), (2, 2), (0, 1), False, None),
((1, 2, 3, 5), (2, 2), (2, 2), (1, 0), True, (4, 10)), # H: (3-1)*2-2+2, W: (5-1)*2+2
(
(1, 2, 3, 5),
(2, 2),
(2, 2),
(1, 0),
True,
(4, 10),
), # H: (3-1)*2-2+2, W: (5-1)*2+2
]
_TOLERANCE_MAP = {
......@@ -93,8 +124,14 @@ def parse_test_cases():
"""
test_cases = []
for (input_shape, kernel_size, stride, padding,
use_output_size, output_hw) in _TEST_CASES_DATA:
for (
input_shape,
kernel_size,
stride,
padding,
use_output_size,
output_hw,
) in _TEST_CASES_DATA:
indices_high = _kernel_elems_2d(kernel_size)
......
test/infinicore/ops/max_unpool3d.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
from framework.tensor import TensorInitializer
# ==============================================================================
......@@ -32,33 +31,31 @@ _TEST_CASES_DATA = [
# ========== Basic cases ==========
# small sizes with different stride/padding and optional output_size
((1, 1, 4, 4, 4), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((2, 3, 2, 4, 4), (2, 2, 2), None, None, False, None), # default stride / padding
((2, 3, 2, 4, 4), (2, 2, 2), None, None, False, None), # default stride / padding
((2, 3, 4, 4, 4), (3, 3, 3), (2, 2, 2), (1, 1, 1), False, None),
((2, 3, 4, 4, 4), (3, 3, 3), (2, 2, 2), (1, 1, 1), True, (7, 7, 7)),
((2, 3, 4, 4, 4), (3, 3, 3), (2, 2, 2), (1, 1, 1), True, (7, 7, 7)),
((1, 4, 3, 5, 7), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((1, 4, 3, 5, 7), (2, 2, 2), None, (1, 1, 1), True, (4, 8, 12)),
((1, 4, 3, 5, 7), (2, 2, 2), None, (1, 1, 1), True, (4, 8, 12)),
# ========== Large-scale performance test cases ==========
# larger volumes and batches for performance and stability
((4, 8, 8, 16, 16), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((4, 8, 8, 16, 16), (3, 3, 3), (2, 2, 2), (1, 1, 1), False, None),
((8, 16, 4, 32, 32), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((8, 16, 4, 32, 32), (2, 2, 2), (2, 2, 2), (0, 0, 0), True, (8, 64, 64)),
((8, 16, 4, 32, 32), (3, 3, 3), (2, 2, 2), (1, 1, 1), True, (7, 63, 63)),
((4, 8, 8, 16, 16), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((4, 8, 8, 16, 16), (3, 3, 3), (2, 2, 2), (1, 1, 1), False, None),
((8, 16, 4, 32, 32), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((8, 16, 4, 32, 32), (2, 2, 2), (2, 2, 2), (0, 0, 0), True, (8, 64, 64)),
((8, 16, 4, 32, 32), (3, 3, 3), (2, 2, 2), (1, 1, 1), True, (7, 63, 63)),
((2, 32, 16, 16, 16), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((2, 32, 16, 16, 16), (2, 2, 2), None, None, False, None),
((2, 32, 8, 32, 32), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((2, 32, 8, 32, 32), (3, 3, 3), (2, 2, 2), (1, 1, 1), False, None),
((1, 64, 8, 64, 64), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((1, 64, 8, 64, 64), (2, 2, 2), (2, 2, 2), (0, 0, 0), True, (16, 128, 128)),
((2, 32, 16, 16, 16), (2, 2, 2), None, None, False, None),
((2, 32, 8, 32, 32), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((2, 32, 8, 32, 32), (3, 3, 3), (2, 2, 2), (1, 1, 1), False, None),
((1, 64, 8, 64, 64), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((1, 64, 8, 64, 64), (2, 2, 2), (2, 2, 2), (0, 0, 0), True, (16, 128, 128)),
((1, 64, 4, 64, 128), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
# ========== Edge cases ==========
# very small shapes and asymmetric sizes
((1, 1, 1, 1, 1), (1, 1, 1), (1, 1, 1), (0, 0, 0), False, None),
((1, 1, 1, 2, 2), (2, 2, 2), (2, 2, 2), (0, 0, 0), True, (2, 4, 4)),
((1, 1, 1, 2, 2), (2, 2, 2), (2, 2, 2), (0, 0, 0), True, (2, 4, 4)),
((1, 1, 2, 2, 8), (2, 2, 2), (2, 2, 2), (0, 0, 0), False, None),
((1, 1, 2, 2, 8), (2, 2, 2), (2, 2, 2), (1, 1, 1), True, (2, 2, 14)),
((1, 1, 2, 2, 8), (2, 2, 2), (2, 2, 2), (1, 1, 1), True, (2, 2, 14)),
]
_TOLERANCE_MAP = {
......@@ -90,8 +87,14 @@ def parse_test_cases():
"""
test_cases = []
for (input_shape, kernel_size, stride, padding,
use_output_size, output_dhw) in _TEST_CASES_DATA:
for (
input_shape,
kernel_size,
stride,
padding,
use_output_size,
output_dhw,
) in _TEST_CASES_DATA:
indices_high = _kernel_elems_3d(kernel_size)
......
test/infinicore/ops/maximum.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (shape, a_strides, b_strides)
_TEST_CASES_DATA = [
......
test/infinicore/ops/mean.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (in_shape, in_strides_or_None, dim_or_None, keepdim_or_None, out_strides_or_None)
# mean computes average along dimension(s) or overall
......
test/infinicore/ops/median.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (in_shape, in_strides_or_None, dim_or_None, keepdim_or_None, out_strides_or_None)
# median can return median values (and indices when dim is provided)
......
test/infinicore/ops/min.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (in_shape, in_strides_or_None, dim_or_None, keepdim_or_None, out_strides_or_None)
# min reduces by taking minimum along dim(s) or overall
......
test/infinicore/ops/minimum.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (shape, a_strides, b_strides)
_TEST_CASES_DATA = [
......
test/infinicore/ops/mish.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (in_shape, in_strides_or_None)
......
test/infinicore/ops/mse_loss.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
# Test cases format: (input_shape, target_shape, input_strides_or_None, reduction_or_None)
# infinicore.nn.functional.mse_loss(input, target, reduction='mean')
......
test/infinicore/ops/msort.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (shape, input_strides)
_TEST_CASES_DATA = [
......
test/infinicore/ops/mul.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# ==============================================================================
# Operator-specific configuration
......
test/infinicore/ops/multi_margin_loss.py
View file @ 61a7dc0e
......@@ -6,8 +6,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import torch.nn.functional as F
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
from framework.tensor import TensorInitializer
# ==============================================================================
......
test/infinicore/ops/multilabel_margin_loss.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
from framework.tensor import TensorInitializer
# Test cases format: (input_shape_N_C, target_shape_N_C, input_strides_or_None, reduction_or_None)
......
test/infinicore/ops/multilabel_soft_margin_loss.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
# Test cases format: (input_shape, target_shape, input_strides_or_None, reduction_or_None)
# infinicore.nn.functional.multilabel_soft_margin_loss(input, target, reduction='mean')
......
test/infinicore/ops/mv.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (mat_shape, vec_shape, mat_strides_or_None, vec_strides_or_None)
# mv(mat, vec, out=None)
......
test/infinicore/ops/narrow.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
# Test cases format: (input_shape, input_strides_or_None, dim, start, length)
_TEST_CASES_DATA = [
......
test/infinicore/ops/narrow_copy.py
View file @ 61a7dc0e
......@@ -5,9 +5,13 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework.utils import is_broadcast
from framework import (
BaseOperatorTest,
TensorSpec,
TestCase,
GenericTestRunner,
is_broadcast,
)
# Test cases format: (input_shape, input_strides_or_None, dim, start, length)
_TEST_CASES_DATA = [
......
test/infinicore/ops/nll_loss.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
from framework.tensor import TensorInitializer
# Test cases format: (input_shape_N_C, target_shape_N, input_strides_or_None, weight_present_bool, ignore_index_or_None)
......
test/infinicore/ops/nonzero.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
# Test cases format: (input_shape, input_strides_or_None)
# nonzero returns indices of non-zero elements; output is N x ndim indices
......
test/infinicore/ops/normalize.py
View file @ 61a7dc0e
......@@ -5,8 +5,7 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
import torch
import infinicore
from framework.base import BaseOperatorTest, TensorSpec, TestCase
from framework.runner import GenericTestRunner
from framework import BaseOperatorTest, TensorSpec, TestCase, GenericTestRunner
# Test cases format: (input_shape, input_strides_or_None, p_or_None, dim_or_None, eps_or_None)
# infinicore.nn.functional.normalize(input, p=2.0, dim=1, eps=1e-12)
......
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