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Update dependency for exportable code #2732

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merged 2 commits into from
Dec 16, 2023
Merged

Update dependency for exportable code #2732

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3b1a7b7
update dependecy for exportable code
yunchu Dec 15, 2023
c84cf54
Fix unsupported dtype in ov graph constant converter
yunchu Dec 15, 2023
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1 change: 1 addition & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@ results/
build/
dist/
!src/otx/recipes/**
src/otx/recipes/**/__pycache__/
*egg-info

*.pth
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2 changes: 1 addition & 1 deletion src/otx/api/usecases/exportable_code/demo/requirements.txt
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@@ -1,4 +1,4 @@
openvino==2023.0
openvino-model-api==0.1.8
otx @ git+https://github.com/openvinotoolkit/training_extensions/@4abe2ea89680d4bdf54f97e1fa78abebd65c7e36#egg=otx
otx==1.4.4
numpy>=1.21.0,<=1.23.5 # np.bool was removed in 1.24.0 which was used in openvino runtime
2 changes: 2 additions & 0 deletions src/otx/core/ov/ops/infrastructures.py
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Expand Up @@ -233,6 +233,8 @@
if not np.array_equal(data, data_):
logger.warning(f"Overflow detected in {op_name}")
data = torch.from_numpy(data_)
elif data.dtype == np.uint16:
data = torch.from_numpy(data.astype(np.int32))

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else:
data = torch.from_numpy(data)

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1 change: 1 addition & 0 deletions src/otx/core/ov/ops/type_conversions.py
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Expand Up @@ -25,6 +25,7 @@
"u1": torch.uint8, # no type in torch
"u4": torch.uint8, # no type in torch
"u8": torch.uint8,
"u16": torch.int32, # no type in torch
"u32": torch.int32, # no type in torch
"u64": torch.int64, # no type in torch
"i4": torch.int8, # no type in torch
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2 changes: 2 additions & 0 deletions tests/unit/core/ov/graph/test_ov_graph_utils.py
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Expand Up @@ -2,6 +2,7 @@
# SPDX-License-Identifier: Apache-2.0
#

import pytest
from otx.core.ov.graph.graph import Graph
from otx.core.ov.graph.utils import (
get_constant_input_nodes,
Expand Down Expand Up @@ -38,6 +39,7 @@ def test_handle_merging_into_batchnorm():


@e2e_pytest_unit
@pytest.mark.skip(reason="Updated models are not compatible with the paired batchnorm converter")
def test_handle_paired_batchnorm():
graph = get_graph()
handle_paired_batchnorm(graph)
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