TensorFlow macOS AutoUpdate (#9471)
* TensorFlow macOS AutoUpdate * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@@ -72,6 +72,8 @@ from utils.general import (LOGGER, Profile, check_dataset, check_img_size, check
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check_yaml, colorstr, file_size, get_default_args, print_args, url2file, yaml_save)
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check_yaml, colorstr, file_size, get_default_args, print_args, url2file, yaml_save)
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from utils.torch_utils import select_device, smart_inference_mode
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from utils.torch_utils import select_device, smart_inference_mode
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MACOS = platform.system() == 'Darwin' # macOS environment
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def export_formats():
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def export_formats():
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# YOLOv5 export formats
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# YOLOv5 export formats
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@@ -224,7 +226,7 @@ def export_coreml(model, im, file, int8, half, prefix=colorstr('CoreML:')):
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ct_model = ct.convert(ts, inputs=[ct.ImageType('image', shape=im.shape, scale=1 / 255, bias=[0, 0, 0])])
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ct_model = ct.convert(ts, inputs=[ct.ImageType('image', shape=im.shape, scale=1 / 255, bias=[0, 0, 0])])
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bits, mode = (8, 'kmeans_lut') if int8 else (16, 'linear') if half else (32, None)
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bits, mode = (8, 'kmeans_lut') if int8 else (16, 'linear') if half else (32, None)
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if bits < 32:
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if bits < 32:
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if platform.system() == 'Darwin': # quantization only supported on macOS
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if MACOS: # quantization only supported on macOS
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with warnings.catch_warnings():
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with warnings.catch_warnings():
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warnings.filterwarnings("ignore", category=DeprecationWarning) # suppress numpy==1.20 float warning
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warnings.filterwarnings("ignore", category=DeprecationWarning) # suppress numpy==1.20 float warning
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ct_model = ct.models.neural_network.quantization_utils.quantize_weights(ct_model, bits, mode)
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ct_model = ct.models.neural_network.quantization_utils.quantize_weights(ct_model, bits, mode)
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@@ -310,8 +312,11 @@ def export_saved_model(model,
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keras=False,
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keras=False,
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prefix=colorstr('TensorFlow SavedModel:')):
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prefix=colorstr('TensorFlow SavedModel:')):
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# YOLOv5 TensorFlow SavedModel export
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# YOLOv5 TensorFlow SavedModel export
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check_requirements('tensorflow' if torch.cuda.is_available() else 'tensorflow-cpu')
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try:
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import tensorflow as tf
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import tensorflow as tf
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except Exception:
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check_requirements(f"tensorflow{'' if torch.cuda.is_available() else '-macos' if MACOS else '-cpu'}")
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import tensorflow as tf
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from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2
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from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2
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from models.tf import TFModel
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from models.tf import TFModel
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+1
-1
@@ -30,7 +30,7 @@ seaborn>=0.11.0
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# nvidia-pyindex # TensorRT export
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# nvidia-pyindex # TensorRT export
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# nvidia-tensorrt # TensorRT export
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# nvidia-tensorrt # TensorRT export
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# scikit-learn==0.19.2 # CoreML quantization
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# scikit-learn==0.19.2 # CoreML quantization
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# tensorflow>=2.4.1 # TFLite export (or tensorflow-cpu, tensorflow-aarch64)
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# tensorflow>=2.4.1 # TF exports (-cpu, -aarch64, -macos)
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# tensorflowjs>=3.9.0 # TF.js export
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# tensorflowjs>=3.9.0 # TF.js export
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# openvino-dev # OpenVINO export
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# openvino-dev # OpenVINO export
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