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[draft] Xiaowu/fix bug(embedding bag) #1099

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Update core.py
xiaowuhu Oct 23, 2023
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Update core.py
xiaowuhu Oct 23, 2023
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Update core.py
xiaowuhu Nov 20, 2023
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Merge branch 'main' into xiaowu/fixBug(embedding_bag)
xiaowuhu Nov 20, 2023
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98 changes: 98 additions & 0 deletions onnxscript/function_libs/torch_lib/ops/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3046,6 +3046,104 @@ def _aten_embedding_bag_1d_padding_idx_onnx(
return result, offset2bag, bag_size, max_indices



def test_embedding_bag_onnx():
import numpy as np

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Code scanning / lintrunner

PYLINT/C0415

Import outside toplevel (numpy) (import-outside-toplevel) See [import-outside-toplevel](https://pylint.pycqa.org/en/latest/user_guide/messages/convention/import-outside-toplevel.html). To disable, use ` # pylint: disable=import-outside-toplevel`
# https://github.com/microsoft/onnxscript/issues/1056
weight = np.array(
[[-2.7199, -1.7691, -8.5981, -5.9605, -3.7100],
[ 0.3334, 3.5580, 5.4002, -6.1015, -3.9192],
[ 3.2690, 7.4735, -1.8522, 6.7348, -1.4507],
[ 0.9523, 8.1493, -8.3490, -5.6658, -2.2785],
[-3.5082, 7.7760, -5.8336, -4.1430, -6.2878],
[-8.4290, -5.2537, 7.7364, 4.0160, 4.3621],
[ 0.4733, -4.6142, 1.5227, -8.4033, -6.5031],
[-4.6398, 5.6784, 5.2769, -3.9915, -0.3247],
[ 5.7560, 8.9472, 3.5719, 1.2158, 6.0344],
[-5.2992, 1.6771, -6.9777, -6.2378, -4.6493]],
dtype=np.float16)
indices = np.array([4, 9, 3, 0, 3], dtype=np.int64)
offsets = np.array([0, 3], dtype=np.int64)
# sample=7
# weight = np.array(
# [[ 1.9951, -1.1777, -3.7695, -3.3125, 8.5078],
# [-3.9648, -3.2617, 4.5430, -6.7500, 1.1953],
# [ 1.8193, -4.9297, 8.3438, 1.2217, 0.0352],
# [-5.2812, -5.9414, -0.7295, 2.4785, -3.8496],
# [ 7.2070, -0.1582, 3.8047, 1.9248, -1.8018]],
# dtype=np.float16)
# indices = np.array([2, 3, 1, 4, 3, 0], dtype=np.int64)
# offsets = np.array([0, 3, 6], dtype=np.int64)
mode = 0 # sum
# include_last_offset = True
per_sample_weights = np.array([2.4134, -0.1783, 7.1360, -0.7987, 2.3815], dtype=np.float16)
#per_sample_weights = np.array([-2.2930, 6.2148, 3.1562, 0.0791, 6.3555], dtype=np.float16)
result1, offset2bag, bag_size, max_indices = aten_embedding_bag(weight, indices, offsets, mode=mode, per_sample_weights=per_sample_weights)

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Code scanning / lintrunner

PYLINT/W0612

Unused variable 'offset2bag' (unused-variable) See [unused-variable](https://pylint.pycqa.org/en/latest/user_guide/messages/warning/unused-variable.html). To disable, use ` # pylint: disable=unused-variable`

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Code scanning / lintrunner

PYLINT/W0612

Unused variable 'bag_size' (unused-variable) See [unused-variable](https://pylint.pycqa.org/en/latest/user_guide/messages/warning/unused-variable.html). To disable, use ` # pylint: disable=unused-variable`

Check warning

Code scanning / lintrunner

PYLINT/W0612

Unused variable 'max_indices' (unused-variable) See [unused-variable](https://pylint.pycqa.org/en/latest/user_guide/messages/warning/unused-variable.html). To disable, use ` # pylint: disable=unused-variable`
result2, offset2bag, bag_size, max_indices = aten_embedding_bag_padding_idx(weight, indices, offsets, mode=mode, per_sample_weights=per_sample_weights)
print("result from onnx-script:")
print(result1)
print(result2)
# print(offset2bag)
# print(bag_size)
# print(max_indices)

def test_embedding_bag_aten():
import torch as t

weight = t.tensor(
[[ 1.9951, -1.1777, -3.7695, -3.3125, 8.5078],
[-3.9648, -3.2617, 4.5430, -6.7500, 1.1953],
[ 1.8193, -4.9297, 8.3438, 1.2217, 0.0352],
[-5.2812, -5.9414, -0.7295, 2.4785, -3.8496],
[ 7.2070, -0.1582, 3.8047, 1.9248, -1.8018]],
dtype=t.float16)

indices = t.tensor([2, 3, 1, 4, 3, 0],
dtype=t.int64)

mode = 0

offsets = t.tensor([0, 3, 6], dtype=t.int64)
mode = 0 # sum
include_last_offset = True
#per_sample_weights = t.tensor([-2.2930, 6.2148, 3.1562, 0.0791, 6.3555], dtype=t.float16)

result, offset2bag, bag_size, max_indices = t.ops.aten.embedding_bag(weight, indices, offsets, mode=mode, include_last_offset=include_last_offset)
print("result from aten:")
print(result)
print(offset2bag)
print(bag_size)
print(max_indices)

def test_embedding_bag_nn_function():
import torch as t
weight = t.tensor(
[[-6.5664, 6.6250, 7.0664, -3.7344, 0.6152],
[ 4.1484, -3.7266, 3.4805, -6.2422, -2.8047],
[ 4.2734, -4.1562, -8.2344, -7.4688, 5.2734],
[-1.5381, 5.9492, -4.2812, -1.5732, -8.3672],
[-2.1719, 8.0469, -7.9883, -0.4219, -2.3633],
[ 6.2305, 8.9844, 7.4453, 3.7891, -5.0625],
[-1.5293, -8.1328, 8.6484, 1.5557, -2.3633],
[-1.9951, -3.2070, 1.2920, -1.0020, -5.2812],
[ 2.5312, 8.4453, 2.3281, -2.8750, -3.3828],
[-4.2188, -4.2266, -2.7246, -6.8555, -7.6719]], dtype=t.float16)
indices = t.tensor([4, 9, 3, 0, 3], dtype=t.int64)
offsets = t.tensor([0, 3], dtype=t.int64)
mode = 0 # sum
per_sample_weights = t.tensor([-2.2930, 6.2148, 3.1562, 0.0791, 6.3555], dtype=t.float16)
result = t.nn.functional.embedding_bag(indices, weight, offsets=offsets, mode="sum", per_sample_weights=per_sample_weights)
print("result from nn.functional:")
print(result)


test_embedding_bag_onnx()
#test_embedding_bag_aten()
#test_embedding_bag_nn_function()

exit(0)

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Code scanning / lintrunner

PYLINT/R1722

Consider using 'sys.exit' instead (consider-using-sys-exit) See [consider-using-sys-exit](https://pylint.pycqa.org/en/latest/user_guide/messages/refactor/consider-using-sys-exit.html). To disable, use ` # pylint: disable=consider-using-sys-exit`


def aten_embedding_dense_backward(
grad_output: TensorType,
indices: TensorType,
Expand Down