natas_hw
/
openvino
0
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Add test case to verify 4bit precision input model. (#24774) 

### Details:
- *Complete the remaining work after the
[PR](https://github.com/openvinotoolkit/openvino/pull/24297) is merged.*
 - *Add test case.*

### Tickets:
 - *141542*

---------

Signed-off-by: xipingya <xiping.yan@intel.com>
Co-authored-by: Zlobin Vladimir <vladimir.zlobin@intel.com>
This commit is contained in:
Xiping Yan 2024-06-06 11:23:26 +08:00 committed by GitHub
parent b1bc59e72d
commit e922edf299
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
4 changed files with 67 additions and 25 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
src/plugins/intel_cpu/src/nodes/common/cpu_convert.cpp
View File

@ -590,8 +590,8 @@ struct ConvertFromBinPrecision {
#define INTEL_CPU_CVT_FROM_4BIT(DT) OV_CASE(ov::element::DT, PrecisionInfo<ov::element::DT>::value_type)
#define INTEL_CPU_CVT_FROM_4BIT_LIST \
INTEL_CPU_CVT_FROM_4BIT(f32), INTEL_CPU_CVT_FROM_4BIT(bf16), INTEL_CPU_CVT_FROM_4BIT(i8), \
INTEL_CPU_CVT_FROM_4BIT(u8)
INTEL_CPU_CVT_FROM_4BIT(f32), INTEL_CPU_CVT_FROM_4BIT(bf16), INTEL_CPU_CVT_FROM_4BIT(f16), \
INTEL_CPU_CVT_FROM_4BIT(i8), INTEL_CPU_CVT_FROM_4BIT(u8)
struct ConvertFrom4BitContext {
ov::element::Type_t inType;

18
tests/samples_tests/smoke_tests/common/samples_common_test_class.py
View File

@ -26,6 +26,7 @@ import zipfile
import logging as log
from common.common_utils import shell
from shutil import which
import openvino.runtime as ov
log.basicConfig(format="[ %(levelname)s ] %(message)s", level=log.INFO, stream=sys.stdout)
@ -75,13 +76,24 @@ def download(test_data_dir, file_path):
time.sleep(1.0)
def prepend(cache, inp='', model=''):
def prepend(cache, inp='', model='', tmp_path=None):
test_data_dir = cache.mkdir('test_data')
if inp:
inp = '-i', download(test_data_dir, test_data_dir / inp)
if model:
if type(model) is ov.ie_api.Model:
model_sv_path = tmp_path / "model_with_4bit_input.xml"
ov.save_model(model, model_sv_path)
model = '-m', model_sv_path
else:
model = '-m', download(test_data_dir, test_data_dir / model)
if inp:
if os.path.exists(tmp_path / inp):
inp = '-i', tmp_path / inp
else:
inp = '-i', download(test_data_dir, test_data_dir / inp)
return *inp, *model
else:
return *model,
def get_tests(cmd_params, use_device=True, use_batch=False):

50
tests/samples_tests/smoke_tests/test_benchmark_app.py
View File

@ -12,10 +12,12 @@
"""
import json
import os
import numpy as np
import pathlib
import pytest
from common.samples_common_test_class import get_devices, get_cmd_output, prepend
from openvino.runtime import opset8 as opset
import openvino.runtime as ov
def get_executable(sample_language):
executable = 'benchmark_app'
@ -25,11 +27,21 @@ def get_executable(sample_language):
return executable
return 'benchmark_app'
def create_random_4bit_bin_file(tmp_path, shape, name):
fullname = tmp_path / name
rs = np.random.RandomState(np.random.MT19937(np.random.SeedSequence(0)))
pack_shape = [x for x in shape]
pack_shape[-1] = pack_shape[-1]*4
rand_data = (rs.uniform(0, 15, list(pack_shape)) >= 7).astype(int).flatten()
raw_data = np.packbits(rand_data)
with open(fullname, "wb") as f:
f.write(raw_data)
def verify(sample_language, device, api=None, nireq=None, shape=None, data_shape=None, nstreams=None, layout=None, pin=None, cache=None, tmp_path=None, model='bvlcalexnet-12.onnx'):
def verify(sample_language, device, api=None, nireq=None, shape=None, data_shape=None, nstreams=None, layout=None, pin=None, cache=None, tmp_path=None, model='bvlcalexnet-12.onnx', inp='dog-224x224.bmp', batch='1', niter='10', tm=None):
output = get_cmd_output(
get_executable(sample_language),
*prepend(cache, 'dog-224x224.bmp', model),
*prepend(cache, inp, model, tmp_path),
*('-nstreams', nstreams) if nstreams else '',
*('-layout', layout) if layout else '',
*('-nireq', nireq) if nireq else '',
@ -40,7 +52,10 @@ def verify(sample_language, device, api=None, nireq=None, shape=None, data_shape
*('-api', api) if api else '',
*('-dump_config', tmp_path / 'conf.json') if tmp_path else '',
*('-exec_graph_path', tmp_path / 'exec_graph.xml') if tmp_path else '',
'-d', device, '-b', '1', '-niter', '10'
*('-b', batch) if batch else '',
*('-niter', niter) if niter else '10',
*('-t', tm) if tm else '',
'-d', device
)
assert 'FPS' in output
if tmp_path:
@ -65,8 +80,8 @@ def test_benchmark_app_help(sample_language):
@pytest.mark.parametrize('api', ['sync', 'async'])
@pytest.mark.parametrize('nireq', ['4', ''])
@pytest.mark.parametrize('device', get_devices())
def test_nireq(sample_language, api, nireq, device, cache):
verify(sample_language, device, api=api, nireq=nireq, cache=cache)
def test_nireq(sample_language, api, nireq, device, cache, tmp_path):
verify(sample_language, device, api=api, nireq=nireq, cache=cache, tmp_path=tmp_path)
@pytest.mark.skipif('CPU' not in get_devices(), reason='affinity is a CPU property')
@ -91,11 +106,26 @@ def test_api(sample_language, api, device, cache, tmp_path):
@pytest.mark.parametrize('sample_language', ['C++', 'Python'])
@pytest.mark.parametrize('device', get_devices())
def test_reshape(sample_language, device, cache):
verify(sample_language, device, shape='data_0[2,3,224,224]', cache=cache)
def test_reshape(sample_language, device, cache, tmp_path):
verify(sample_language, device, shape='data_0[2,3,224,224]', cache=cache, tmp_path=tmp_path)
@pytest.mark.parametrize('sample_language', ['C++', 'Python'])
@pytest.mark.parametrize('device', get_devices())
def test_dynamic_shape(sample_language, device, cache):
verify(sample_language, device, model='efficientnet-lite4-11-qdq.onnx', shape='[?,224,224,3]', data_shape='[1,224,224,3][2,224,224,3]', layout='[NHWC]', cache=cache)
def test_dynamic_shape(sample_language, device, cache, tmp_path):
verify(sample_language, device, model='efficientnet-lite4-11-qdq.onnx',
shape='[?,224,224,3]', data_shape='[1,224,224,3][2,224,224,3]', layout='[NHWC]', cache=cache, tmp_path=tmp_path)
@pytest.mark.parametrize('sample_language', ['C++', 'Python'])
@pytest.mark.parametrize('device', ['CPU'])
@pytest.mark.parametrize('inp', [None, 'random_4bit_data.bin'])
def test_4bit_precision_input(sample_language, device, inp, cache, tmp_path):
inp_type = ov.Type.i4
inp_shape = [128] # only pass scalar.
input = opset.parameter(inp_shape, inp_type, name='in')
cvt = opset.convert(input, ov.Type.f32)
result = opset.result(cvt, name='cvt')
model_4bit = ov.Model([result], [input], 'model_with_4bit_input')
if inp != None and inp.endswith(".bin"):
create_random_4bit_bin_file(tmp_path, inp_shape, inp)
verify(sample_language, device, model=model_4bit, inp=inp, cache=cache, tmp_path=tmp_path, batch=None, tm='1')

14
tools/benchmark_tool/openvino/tools/benchmark/utils/inputs_filling.py
View File

@ -291,7 +291,7 @@ def get_binary_tensors(binary_paths: List[str], info: AppInputInfo, batch_sizes:
tensors = []
for i in range(niter):
shape_id = i % num_shapes
dtype = get_dtype(info.element_type)
dtype = np.uint8() if info.element_type.bitwidth < 8 else get_dtype(info.element_type)
shape = list(info.shapes[shape_id])
binaries = np.ndarray(shape=shape, dtype=dtype)
binary_index = processed_frames
@ -301,12 +301,12 @@ def get_binary_tensors(binary_paths: List[str], info: AppInputInfo, batch_sizes:
binary_filename: str = binary_paths[binary_index]
extension = binary_filename.lower().split('.')[-1]
if extension == "bin":
binary_file_size = os.path.getsize(binary_filename)
blob_size = dtype.itemsize * int(np.prod(shape))
if blob_size != binary_file_size:
binary_file_bit_size = os.path.getsize(binary_filename) * 8
blob_bit_size = info.element_type.bitwidth * int(np.prod(shape))
if blob_bit_size != binary_file_bit_size:
raise Exception(
f"File {binary_filename} contains {binary_file_size} bytes but model expects {blob_size}")
from_file = np.reshape(np.fromfile(binary_filename, dtype), shape)
f"File {binary_filename} contains {binary_file_bit_size} bites but model expects {blob_bit_size}")
from_file = np.fromfile(binary_filename, dtype)
if info.layout.has_name("N"):
binaries[[None] * info.layout.get_index_by_name("N") + [b]] = from_file
else:
@ -317,7 +317,7 @@ def get_binary_tensors(binary_paths: List[str], info: AppInputInfo, batch_sizes:
binary_index += 1
processed_frames += current_batch_size
tensors.append(Tensor(binaries))
tensors.append(Tensor(binaries, shape, info.element_type))
return tensors