From f3891cda50a3bf75cd57dcfaeae4eb13e4231bf1 Mon Sep 17 00:00:00 2001 From: Nikita Savelyev Date: Tue, 29 Oct 2024 16:18:32 +0100 Subject: [PATCH] Comment out env vars --- .../algorithms/weight_compression/weight_lowering.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/nncf/quantization/algorithms/weight_compression/weight_lowering.py b/nncf/quantization/algorithms/weight_compression/weight_lowering.py index 265b624c872..3eaa024f4c2 100644 --- a/nncf/quantization/algorithms/weight_compression/weight_lowering.py +++ b/nncf/quantization/algorithms/weight_compression/weight_lowering.py @@ -461,7 +461,7 @@ def do_int_quantization( accelerate_through_ov = ( is_openvino_available() and weight.backend != TensorBackend.torch - and not bool(int(os.environ.get("NUMPY_COMPRESSION", "0"))) + # and not bool(int(os.environ.get("NUMPY_COMPRESSION", "0"))) ) if not is_openvino_available() and weight.backend != TensorBackend.torch: log_once(logging.INFO, "Compression time may be improved after installing OpenVINO") @@ -502,10 +502,10 @@ def do_int_quantization( ov_model_params.return_ov_tensors = weight.backend == TensorBackend.ov else: ov_model_params.output_dtype = TensorDataType.uint8 if config.is_int_asym else TensorDataType.int8 - ov_model_params.dynamic_shapes = bool(int(os.environ.get("DYNAMIC_COMPRESSION", "0"))) - ov_model_params.recompile = bool(int(os.environ.get("RECOMPILE", "0"))) - ov_model_params.release_memory = bool(int(os.environ.get("RELEASE_MEMORY", "0"))) - ov_model_params.share_outputs = bool(int(os.environ.get("SHARE_OUTPUTS", "0"))) + # ov_model_params.dynamic_shapes = bool(int(os.environ.get("DYNAMIC_COMPRESSION", "0"))) + # ov_model_params.recompile = bool(int(os.environ.get("RECOMPILE", "0"))) + # ov_model_params.release_memory = bool(int(os.environ.get("RELEASE_MEMORY", "0"))) + # ov_model_params.share_outputs = bool(int(os.environ.get("SHARE_OUTPUTS", "0"))) model = get_compress_weight_model( ov_model_params, @@ -557,7 +557,7 @@ def calculate_quantized_dequantized_weight( accelerate_through_ov = ( is_openvino_available() and weight.backend != TensorBackend.torch - and not bool(int(os.environ.get("NUMPY_COMPRESSION", "0"))) + # and not bool(int(os.environ.get("NUMPY_COMPRESSION", "0"))) ) if not is_openvino_available() and weight.backend != TensorBackend.torch: log_once(logging.INFO, "Compression time may be improved after installing OpenVINO")