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Diffstat (limited to 'verif/generator/datagenerator.py')
-rw-r--r-- | verif/generator/datagenerator.py | 196 |
1 files changed, 196 insertions, 0 deletions
diff --git a/verif/generator/datagenerator.py b/verif/generator/datagenerator.py new file mode 100644 index 0000000..408c83e --- /dev/null +++ b/verif/generator/datagenerator.py @@ -0,0 +1,196 @@ +# Copyright (c) 2023, ARM Limited. +# SPDX-License-Identifier: Apache-2.0 +"""Calls the data generation library to create the test data.""" +import ctypes as ct +import json +from pathlib import Path + +import numpy as np +from schemavalidation import schemavalidation + + +class GenerateError(Exception): + """Exception raised for errors performing data generation.""" + + +class GenerateLibrary: + """Python interface to the C generate library.""" + + def __init__(self, generate_lib_path): + """Find the library and set up the interface.""" + self.lib_path = generate_lib_path + if not self.lib_path.is_file(): + raise GenerateError(f"Could not find generate library - {self.lib_path}") + + self.test_desc = None + self.json_config = None + self.lib = ct.cdll.LoadLibrary(self.lib_path) + + self.tgd_generate_data = self.lib.tgd_generate_data + self.tgd_generate_data.argtypes = [ + ct.c_char_p, + ct.c_char_p, + ct.c_void_p, + ct.c_size_t, + ] + self.tgd_generate_data.restype = ct.c_bool + + def check_config(self, test_desc: dict): + """Quick check that the config supports data generation.""" + return ("meta" in test_desc) and ("data_gen" in test_desc["meta"]) + + def set_config(self, test_desc: dict): + """Set the test config in the library. + + test_desc - the test desc.json file + """ + self.test_desc = None + self.json_config = None + + if not self.check_config(test_desc): + raise GenerateError("No meta/data_gen section found in desc.json") + + # Validate the config versus the schema + tdsv = schemavalidation.TestDescSchemaValidator() + tdsv.validate_config(test_desc) + + self.test_desc = test_desc + self.json_config = test_desc["meta"]["data_gen"] + + def _create_buffer(self, dtype: str, shape: tuple): + """Helper to create a buffer of the required type.""" + size = 1 + for dim in shape: + size *= dim + + if dtype == "FP32": + # Create buffer and initialize to zero + buffer = (ct.c_float * size)(0) + size_bytes = size * 4 + else: + raise GenerateError(f"Unsupported data type {dtype}") + + return buffer, size_bytes + + def _data_gen_write( + self, test_path: Path, json_bytes: bytes, ifm_name: str, ifm_file: str + ): + """Generate the named tensor data and save it in numpy format.""" + try: + tensor = self.json_config["tensors"][ifm_name] + dtype = tensor["data_type"] + shape = tuple(tensor["shape"]) + except KeyError as e: + raise GenerateError( + f"Missing data in desc.json for input {ifm_name} - {repr(e)}" + ) + + buffer, size_bytes = self._create_buffer(dtype, shape) + buffer_ptr = ct.cast(buffer, ct.c_void_p) + + result = self.tgd_generate_data( + ct.c_char_p(json_bytes), + ct.c_char_p(bytes(ifm_name, "utf8")), + buffer_ptr, + ct.c_size_t(size_bytes), + ) + if not result: + raise GenerateError("Data generate failed") + + arr = np.ctypeslib.as_array(buffer) + arr = np.reshape(arr, shape) + + file_name = test_path / ifm_file + np.save(file_name, arr) + + def write_numpy_files(self, test_path: Path): + """Write out all the specified tensors to numpy data files.""" + if self.test_desc is None or self.json_config is None: + raise GenerateError("Cannot write numpy files as no config set up") + + try: + ifm_names = self.test_desc["ifm_name"] + ifm_files = self.test_desc["ifm_file"] + except KeyError as e: + raise GenerateError(f"Missing data in desc.json - {repr(e)}") + + json_bytes = bytes(json.dumps(self.json_config), "utf8") + + failures = [] + for iname, ifile in zip(ifm_names, ifm_files): + try: + self._data_gen_write(test_path, json_bytes, iname, ifile) + except GenerateError as e: + failures.append( + f"ERROR: Failed to create data for tensor {iname} - {repr(e)}" + ) + + if len(failures) > 0: + raise GenerateError("\n".join(failures)) + + +def main(argv=None): + """Simple command line interface for the data generator.""" + import argparse + import conformance.model_files as cmf + + parser = argparse.ArgumentParser() + parser.add_argument( + "--generate-lib-path", + type=Path, + help="Path to TOSA generate lib", + ) + parser.add_argument( + "path", type=Path, help="the path to the test directory to generate data for" + ) + args = parser.parse_args(argv) + test_path = args.path + + if args.generate_lib_path is None: + # Try to work out ref model directory and find the verify library + # but this default only works for the python developer environment + # i.e. when using the scripts/py-dev-env.* scripts + # otherwise use the command line option --generate-lib-path to specify path + ref_model_dir = Path(__file__).absolute().parents[2] + args.generate_lib_path = cmf.find_tosa_file( + cmf.TosaFileType.GENERATE_LIBRARY, ref_model_dir, False + ) + + if not test_path.is_dir(): + print(f"ERROR: Invalid directory - {test_path}") + return 2 + + test_desc_path = test_path / "desc.json" + + if not test_desc_path.is_file(): + print(f"ERROR: No test description found: {test_desc_path}") + return 2 + + # Load the JSON desc.json + try: + with test_desc_path.open("r") as fd: + test_desc = json.load(fd) + except Exception as e: + print(f"ERROR: Loading {test_desc_path} - {repr(e)}") + return 2 + + try: + dgl = GenerateLibrary(args.generate_lib_path) + if not dgl.check_config(test_desc): + print(f"WARNING: No data generation supported for {test_path}") + return 2 + + dgl.set_config(test_desc) + except GenerateError as e: + print(f"ERROR: Initializing generate library - {repr(e)}") + return 1 + + try: + dgl.write_numpy_files(test_path) + except GenerateError as e: + print(f"ERROR: Writing out data files to {test_path}\n{repr(e)}") + return 1 + + +if __name__ == "__main__": + exit(main()) |