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[MO] compress_to_fp16=False by default (#16854)

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* compress_to_fp16=False by default

* Apply suggestions from code review

Co-authored-by: Karol Blaszczak <karol.blaszczak@intel.com>

* note abound RAM consumption for FP16 compressed models

* detailed notion about RAM usage

* update 'get_compression_message()'

* corrected get_compression_message: remove infor about RAM

* fix pytorch convert layer tests

---------

Co-authored-by: Karol Blaszczak <karol.blaszczak@intel.com>
This commit is contained in:
Pavel Esir
2023-04-14 03:16:41 +02:00
committed by GitHub
parent de8f34c8f0
commit 68f46ff9a1
4 changed files with 30 additions and 35 deletions
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38
tests/layer_tests/mo_python_api_tests/test_mo_convert_pytorch.py
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@@ -458,23 +458,18 @@ def create_pytorch_nn_module_mean_list(tmp_dir):
"input": [InputCutInfo("x", None, "f32", None), InputCutInfo("y", None, "f32", None)]}
def create_pytorch_nn_module_mean_list_default_compression(tmp_dir):
# by default compression should be enabled (same as setting 'compress_to_fp16': True)
# therefore decompression Converts will be present
def create_pytorch_nn_module_mean_list_default_no_compression(tmp_dir):
# by default compression is disabled (same as setting 'compress_to_fp16': False)
pt_model = make_pt_model_two_inputs()
shape = [1, 10, 10, 3]
shape = PartialShape(shape)
param1 = ov.opset8.parameter(shape)
param2 = ov.opset8.parameter(shape)
const1 = ov.opset8.constant([[[[0, 0, 0]]]], dtype=np.float16)
const1_decompressed = ov.opset8.convert(
const1, destination_type=np.float32)
const2 = ov.opset8.constant([[[[0, 0, 0]]]], dtype=np.float16)
const2_decompressed = ov.opset8.convert(
const2, destination_type=np.float32)
sub1 = ov.opset8.subtract(param1, const1_decompressed)
sub2 = ov.opset8.subtract(param2, const2_decompressed)
const1 = ov.opset8.constant([[[[0, 0, 0]]]], dtype=np.float32)
const2 = ov.opset8.constant([[[[0, 0, 0]]]], dtype=np.float32)
sub1 = ov.opset8.subtract(param1, const1)
sub2 = ov.opset8.subtract(param2, const2)
add = ov.opset8.add(sub1, sub2)
relu = ov.opset8.relu(add)
sigm = ov.opset8.sigmoid(relu)
@@ -529,23 +524,18 @@ def create_pytorch_nn_module_scale_list(tmp_dir):
return pt_model, ref_model, {'input_shape': [shape, shape], 'scale_values': [[1, 1, 1], [1, 1, 1]], 'compress_to_fp16': False, "input": [InputCutInfo("x", None, "f32", None), InputCutInfo("y", None, "f32", None)]}
def create_pytorch_nn_module_scale_list_default_compression(tmp_dir):
# by default compression should be enabled (same as setting 'compress_to_fp16': True)
# therefore decompression Converts will be present
def create_pytorch_nn_module_scale_list_default_no_compression(tmp_dir):
# by default compression is disabled (same as setting 'compress_to_fp16': False)
pt_model = make_pt_model_two_inputs()
shape = [1, 10, 10, 3]
shape = PartialShape(shape)
param1 = ov.opset8.parameter(shape)
param2 = ov.opset8.parameter(shape)
const1 = ov.opset8.constant([[[[1, 1, 1]]]], dtype=np.float16)
const1_decompressed = ov.opset8.convert(
const1, destination_type=np.float32)
const2 = ov.opset8.constant([[[[1, 1, 1]]]], dtype=np.float16)
const2_decompressed = ov.opset8.convert(
const2, destination_type=np.float32)
sub1 = ov.opset8.multiply(param1, const1_decompressed)
sub2 = ov.opset8.multiply(param2, const2_decompressed)
const1 = ov.opset8.constant([[[[1, 1, 1]]]], dtype=np.float32)
const2 = ov.opset8.constant([[[[1, 1, 1]]]], dtype=np.float32)
sub1 = ov.opset8.multiply(param1, const1)
sub2 = ov.opset8.multiply(param2, const2)
add = ov.opset8.add(sub1, sub2)
relu = ov.opset8.relu(add)
sigm = ov.opset8.sigmoid(relu)
@@ -754,10 +744,10 @@ class TestMoConvertPyTorch(CommonMOConvertTest):
create_pytorch_nn_module_layout_list,
create_pytorch_nn_module_layout_list_case2,
create_pytorch_nn_module_mean_list,
create_pytorch_nn_module_mean_list_default_compression,
create_pytorch_nn_module_mean_list_default_no_compression,
create_pytorch_nn_module_mean_list_compressin_enabled,
create_pytorch_nn_module_scale_list,
create_pytorch_nn_module_scale_list_default_compression,
create_pytorch_nn_module_scale_list_default_no_compression,
create_pytorch_nn_module_scale_list_compression_enabled,
create_pytorch_nn_module_shapes_list_static,
create_pytorch_nn_module_shapes_list_dynamic,