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TensorFlow macOS AutoUpdate #9471

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Sep 18, 2022
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TensorFlow macOS AutoUpdate #9471

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f8d5b76
TensorFlow macOS AutoUpdate
glenn-jocher Sep 18, 2022
0442454
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Sep 18, 2022
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11 changes: 8 additions & 3 deletions export.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,6 +72,8 @@
check_yaml, colorstr, file_size, get_default_args, print_args, url2file, yaml_save)
from utils.torch_utils import select_device, smart_inference_mode

MACOS = platform.system() == 'Darwin' # macOS environment


def export_formats():
# YOLOv5 export formats
Expand Down Expand Up @@ -224,7 +226,7 @@ def export_coreml(model, im, file, int8, half, prefix=colorstr('CoreML:')):
ct_model = ct.convert(ts, inputs=[ct.ImageType('image', shape=im.shape, scale=1 / 255, bias=[0, 0, 0])])
bits, mode = (8, 'kmeans_lut') if int8 else (16, 'linear') if half else (32, None)
if bits < 32:
if platform.system() == 'Darwin': # quantization only supported on macOS
if MACOS: # quantization only supported on macOS
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=DeprecationWarning) # suppress numpy==1.20 float warning
ct_model = ct.models.neural_network.quantization_utils.quantize_weights(ct_model, bits, mode)
Expand Down Expand Up @@ -310,8 +312,11 @@ def export_saved_model(model,
keras=False,
prefix=colorstr('TensorFlow SavedModel:')):
# YOLOv5 TensorFlow SavedModel export
check_requirements('tensorflow' if torch.cuda.is_available() else 'tensorflow-cpu')
import tensorflow as tf
try:
import tensorflow as tf
except Exception:
check_requirements(f"tensorflow{'' if torch.cuda.is_available() else '-macos' if MACOS else '-cpu'}")
import tensorflow as tf
from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2

from models.tf import TFModel
Expand Down
2 changes: 1 addition & 1 deletion requirements.txt
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Expand Up @@ -30,7 +30,7 @@ seaborn>=0.11.0
# nvidia-pyindex # TensorRT export
# nvidia-tensorrt # TensorRT export
# scikit-learn==0.19.2 # CoreML quantization
# tensorflow>=2.4.1 # TFLite export (or tensorflow-cpu, tensorflow-aarch64)
# tensorflow>=2.4.1 # TF exports (-cpu, -aarch64, -macos)
# tensorflowjs>=3.9.0 # TF.js export
# openvino-dev # OpenVINO export

Expand Down