neural_compressor.utils.utility

quantization auto-tuning config system.

This file specifies default config options for quantization auto-tuning tool. User should not change values in this file. Instead, user should write a config file (in yaml) and use cfg_from_file(yaml_file) to load it and override the default options.

Module Contents

Classes

LazyImport	Lazy import python module till use.
CpuInfo	Get CPU Info.
CaptureOutputToFile	Not displayed in API Docs.
Statistics	The statistics printer.
MODE	Mode: Quantization, Benchmark or Pruning.
GLOBAL_STATE	Access the global model.

Functions

version1_lt_version2(version1, version2)	Check whether version1 is less than version2.
version1_gt_version2(version1, version2)	Check whether version1 is greater than version2.
version1_eq_version2(version1, version2)	Check whether version1 is equal to version2.
version1_gte_version2(version1, version2)	Check whether version1 is greater than version2 or is equal to it.
version1_lte_version2(version1, version2)	Check whether version1 is less than version2 or is equal to it.
singleton(cls)	Not displayed in API Docs.
time_limit(seconds)	Limit the time for context execution.
get_size(obj[, seen])	Recursively finds size of objects.
compute_sparsity(tensor)	Compute the sparsity.
fault_tolerant_file(name)	Make another temporary copy of the file.
equal_dicts(d1, d2[, compare_keys, ignore_keys])	Check whether two dicts are same except for those ignored keys.
dump_elapsed_time([customized_msg])	Get the elapsed time for decorated functions.
combine_histogram(old_hist, arr)	Collect layer histogram for arr and combine it with old histogram.
get_tensor_histogram(tensor_data[, bins])	Get the histogram of the tensor data.
get_all_fp32_data(data)	Get all the fp32 data.
get_tuning_history(tuning_history_path)	Get tuning history.
recover(fp32_model, tuning_history_path, num, **kwargs)	Get offline recover tuned model.
str2array(s)	Get the array of the string.
DequantizeWeight(weight_tensor, min_filter_tensor, ...)	Dequantize the weight with min-max filter tensors.
Dequantize(data, scale_info)	Dequantize the data with the scale_info.
load_data_from_pkl(path, filename)	Load data from local pkl file.
dump_data_to_local(data, path, filename)	Dump data to local as pkl file.
set_random_seed(seed)	Set the random seed in config.
set_workspace(workspace)	Set the workspace in config.
set_resume_from(resume_from)	Set the resume_from in config.
set_tensorboard(tensorboard)	Set the tensorboard in config.
show_memory_info(hint)	Show process full memory.

neural_compressor.utils.utility.version1_lt_version2(version1, version2)

Check whether version1 is less than version2.

neural_compressor.utils.utility.version1_gt_version2(version1, version2)

Check whether version1 is greater than version2.

neural_compressor.utils.utility.version1_eq_version2(version1, version2)

Check whether version1 is equal to version2.

neural_compressor.utils.utility.version1_gte_version2(version1, version2)

Check whether version1 is greater than version2 or is equal to it.

neural_compressor.utils.utility.version1_lte_version2(version1, version2)

Check whether version1 is less than version2 or is equal to it.

class neural_compressor.utils.utility.LazyImport(module_name)

Lazy import python module till use.

neural_compressor.utils.utility.singleton(cls)

Not displayed in API Docs.

Singleton decorater.

neural_compressor.utils.utility.time_limit(seconds)

Limit the time for context execution.

neural_compressor.utils.utility.get_size(obj, seen=None)

Recursively finds size of objects.

neural_compressor.utils.utility.compute_sparsity(tensor)

Compute the sparsity.

Parameters:

tensor – Tensorflow or Pytorch tensor

Returns:

(the original tensor size, number of zero elements, number of non-zero elements)

neural_compressor.utils.utility.fault_tolerant_file(name)

Make another temporary copy of the file.

neural_compressor.utils.utility.equal_dicts(d1, d2, compare_keys=None, ignore_keys=None)

Check whether two dicts are same except for those ignored keys.

class neural_compressor.utils.utility.CpuInfo

Get CPU Info.

neural_compressor.utils.utility.dump_elapsed_time(customized_msg='')

Get the elapsed time for decorated functions.

Parameters:

customized_msg (string, optional) – The parameter passed to decorator. Defaults to None.

neural_compressor.utils.utility.combine_histogram(old_hist, arr)

Collect layer histogram for arr and combine it with old histogram.

neural_compressor.utils.utility.get_tensor_histogram(tensor_data, bins=2048)

Get the histogram of the tensor data.

neural_compressor.utils.utility.get_all_fp32_data(data)

Get all the fp32 data.

neural_compressor.utils.utility.get_tuning_history(tuning_history_path)

Get tuning history.

Parameters:

tuning_history_path – The tuning history path, which need users to assign

neural_compressor.utils.utility.recover(fp32_model, tuning_history_path, num, **kwargs)

Get offline recover tuned model.

Parameters:

• fp32_model – Input model path

• tuning_history_path – The tuning history path, which needs user to assign

• num – tune index

neural_compressor.utils.utility.str2array(s)

Get the array of the string.

neural_compressor.utils.utility.DequantizeWeight(weight_tensor, min_filter_tensor, max_filter_tensor)

Dequantize the weight with min-max filter tensors.

neural_compressor.utils.utility.Dequantize(data, scale_info)

Dequantize the data with the scale_info.

class neural_compressor.utils.utility.CaptureOutputToFile(tmp_file_path, stream=sys.stderr)

Not displayed in API Docs.

Capture the output to file.

class neural_compressor.utils.utility.Statistics(data, header, field_names, output_handle=logger.info)

The statistics printer.

class neural_compressor.utils.utility.MODE

Mode: Quantization, Benchmark or Pruning.

class neural_compressor.utils.utility.GLOBAL_STATE

Access the global model.

neural_compressor.utils.utility.load_data_from_pkl(path, filename)

Load data from local pkl file.

Parameters:

• path – The directory to load data

• filename – The filename to load

neural_compressor.utils.utility.dump_data_to_local(data, path, filename)

Dump data to local as pkl file.

Parameters:

• data – Data used to dump

• path – The directory to save data

• filename – The filename to dump

Returns:

loaded data

neural_compressor.utils.utility.set_random_seed(seed: int)

Set the random seed in config.

neural_compressor.utils.utility.set_workspace(workspace: str)

Set the workspace in config.

neural_compressor.utils.utility.set_resume_from(resume_from: str)

Set the resume_from in config.

neural_compressor.utils.utility.set_tensorboard(tensorboard: bool)

Set the tensorboard in config.

neural_compressor.utils.utility.show_memory_info(hint)

Show process full memory.