| # Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved. |
| # |
| # SPDX-License-Identifier: Apache-2.0 |
| # |
| # Licensed under the Apache License, Version 2.0 (the License); you may |
| # not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an AS IS BASIS, WITHOUT |
| # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # Description: |
| # Main entry point for the Vela compiler. |
| # |
| # Provides command line interface, options parsing, and network loading. Before calling the compiler driver. |
| import argparse |
| import ast |
| import configparser |
| import os.path |
| import sys |
| import time |
| |
| from . import architecture_features |
| from . import compiler_driver |
| from . import model_reader |
| from . import scheduler |
| from . import stats_writer |
| from . import tflite_writer |
| from ._version import __version__ |
| from .api import api_version |
| from .debug_database import DebugDatabase |
| from .errors import InputFileError |
| from .nn_graph import PassPlacement |
| from .nn_graph import TensorAllocator |
| from .scheduler import ParetoMetric |
| from .supported_operators import SupportedOperators |
| from .tensor import MemArea |
| from .tensor import Tensor |
| from .tflite_mapping import builtin_operator_map |
| from .tflite_mapping import builtin_type_name |
| |
| |
| def process(input_name, enable_debug_db, arch, model_reader_options, compiler_options, scheduler_options): |
| if compiler_options.timing: |
| start = time.time() |
| |
| os.makedirs(compiler_options.output_dir, exist_ok=True) |
| output_basename = os.path.join(compiler_options.output_dir, os.path.splitext(os.path.basename(input_name))[0]) |
| DebugDatabase.show_warnings = enable_debug_db |
| |
| nng = model_reader.read_model(input_name, model_reader_options) |
| |
| if not nng: |
| raise InputFileError(input_name, "input file could not be read") |
| |
| if compiler_options.verbose_operators: |
| nng.print_operators() |
| |
| if compiler_options.timing: |
| stop = time.time() |
| print("Model reading took %f s" % (stop - start)) |
| start = time.time() |
| |
| compiler_driver.compiler_driver(nng, arch, compiler_options, scheduler_options) |
| |
| passes_csv_file = "{0}_pass-breakdown_{1}.csv".format(output_basename, arch.system_config) |
| stats_writer.write_pass_metrics_csv(nng, passes_csv_file) |
| |
| summary_csv_file = "{0}_summary_{1}.csv".format(output_basename, arch.system_config) |
| stats_writer.write_summary_metrics_csv(nng, summary_csv_file, arch) |
| |
| stats_writer.print_performance_metrics(nng, show_cpu_operations=compiler_options.show_cpu_operations, arch=arch) |
| |
| output_filename = output_basename + "_vela.tflite" |
| if input_name.endswith(".tflite"): |
| tflite_writer.write_tflite(nng, output_filename) |
| |
| if enable_debug_db: |
| debug_filename = output_basename + "_debug.xml" |
| DebugDatabase.write(debug_filename, input_name, output_filename) |
| |
| if compiler_options.timing: |
| stop = time.time() |
| print("Compiler driver took %f s" % (stop - start)) |
| |
| return nng |
| |
| |
| def print_subgraph_io_summary(nng): |
| """Print a summary of all the input and output tensor sizes for all subgraphs. |
| Also displays the total tensor size and the memory used area for sram. |
| """ |
| |
| print("Subgraph IO Summary") |
| print("-------------------") |
| print("NNG: {0}".format(nng.name)) |
| max_sg_size = 0 |
| for sg in reversed(nng.subgraphs): |
| print(" Subgraph: {0} = {1}".format(sg.name, sg.placement)) |
| sg_size = 0 |
| |
| if sg.placement == PassPlacement.Npu: |
| for tens in sg.input_tensors + [sg.scratch_tensor] + sg.output_tensors: |
| if tens in sg.input_tensors: |
| tens_dir = "In" |
| elif tens in sg.output_tensors: |
| tens_dir = "Out" |
| else: |
| tens_dir = "In/Out" |
| |
| size = tens.elements() * tens.element_size() / 1024.0 |
| sg_size = sg_size + size |
| print(" Tensor [{0}]: {1} = {2} KiB".format(tens_dir, tens.name, size)) |
| |
| print(" Total Size = {0} KiB".format(sg_size)) |
| print(" SRAM Memory Used = {0} KiB".format(sg.memory_used.get(MemArea.Sram, 0) / 1024.0)) |
| max_sg_size = max(sg_size, max_sg_size) |
| |
| print(" Maximum Subgraph Size = {0} KiB".format(max_sg_size)) |
| |
| |
| def generate_supported_ops(): |
| lines = [ |
| "# Supported Ops", |
| "", |
| "This file was automatically generated by Vela using the `--supported-ops-report` parameter. ", |
| f"Vela version: `{__version__}`", |
| "", |
| "This file complies with [**CommonMark.**](https://commonmark.org)", |
| "", |
| "## Summary Table", |
| "", |
| "The table below contains TFLite operators that can be placed on the Ethos-U NPU. ", |
| "If the constraints are not met, then that operator will be scheduled on the CPU instead. ", |
| "For any other TFLite operator not listed, will be left untouched and scheduled on the CPU. ", |
| "Please check the supported operator list for your chosen runtime for further information.", |
| "", |
| "| Operator | Constraints |", |
| "| - | - |", |
| ] |
| supported = SupportedOperators() |
| op_constraint_links = [] |
| op_list = sorted(((op, builtin_type_name(op)) for op in builtin_operator_map), key=lambda x: x[1]) |
| for op, name in op_list: |
| internal_op = builtin_operator_map[op][0] |
| if internal_op in SupportedOperators.supported_operators: |
| links = "[Generic](#generic-constraints)" |
| if internal_op in supported.specific_constraints: |
| links += f", [Specific](#{name.lower()}-constraints)" |
| op_constraint_links.append((internal_op, name)) |
| lines.append(f"| {name} | {links} |") |
| lines += [ |
| "", |
| "## Generic Constraints", |
| "", |
| "This is a list of constraints that all NPU operators must satisfy in order to be scheduled on the NPU.", |
| "", |
| ] |
| for constraint in supported.generic_constraints: |
| # Markdown needs two spaces at the end of a line to render it as a separate line |
| reason = constraint.__doc__.replace("\n", " \n") |
| lines.append(f"- {reason}") |
| for op, name in op_constraint_links: |
| lines += [ |
| "", |
| f"## {name} Constraints", |
| "", |
| f"This is a list of constraints that the {name} operator must satisfy in order to be scheduled on the NPU.", |
| "", |
| ] |
| for constraint in supported.specific_constraints[op]: |
| # Markdown needs two spaces at the end of a line to render it as a separate line |
| reason = constraint.__doc__.replace("\n", " \n") |
| lines.append(f"- {reason}") |
| |
| # Note. this will generate the file in the CWD |
| filepath = os.path.join(os.getcwd(), "SUPPORTED_OPS.md") |
| with open(filepath, "wt") as md: |
| md.writelines(line + "\n" for line in lines) |
| print(f"Report file: {filepath}") |
| |
| |
| def main(args=None): |
| if args is None: |
| args = sys.argv[1:] |
| |
| parser = argparse.ArgumentParser(prog="vela", description="Neural network model compiler for Ethos-U") |
| parser.add_argument("--version", action="version", version=__version__) |
| parser.add_argument( |
| "--api-version", action="version", version=api_version, help="Displays the version of the external API." |
| ) |
| parser.add_argument( |
| "--supported-ops-report", |
| action="store_true", |
| help="Generate the SUPPORTED_OPS.md file in the current working directory and exits.", |
| ) |
| |
| parser.add_argument( |
| "network", metavar="NETWORK", type=str, default=None, nargs="?", help="Filename of network to process" |
| ) |
| |
| parser.add_argument( |
| "--output-dir", type=str, default="output", help="Output directory to write files to (default: %(default)s)" |
| ) |
| parser.add_argument( |
| "--enable-debug-db", |
| action="store_true", |
| default=None, |
| help="Enables the calculation and writing of a network debug database to output directory", |
| ) |
| |
| parser.add_argument("--config", type=str, help="Location of vela configuration file") |
| |
| parser.add_argument("--verbose-graph", action="store_true", help="Verbose graph rewriter") |
| parser.add_argument("--verbose-quantization", action="store_true", help="Verbose quantization") |
| parser.add_argument("--verbose-packing", action="store_true", help="Verbose pass packing") |
| parser.add_argument("--verbose-tensor-purpose", action="store_true", help="Verbose tensor purpose") |
| parser.add_argument("--verbose-tensor-format", action="store_true", help="Verbose tensor format") |
| parser.add_argument("--verbose-schedule", action="store_true", help="Verbose schedule") |
| parser.add_argument( |
| "--verbose-pareto-frontier-schedules", |
| action="store_true", |
| help="Show all schedules along the pareto frontier of optimisation criteria", |
| ) |
| parser.add_argument("--verbose-allocation", action="store_true", help="Verbose tensor allocation") |
| parser.add_argument( |
| "--verbose-high-level-command-stream", action="store_true", help="Verbose high level command stream" |
| ) |
| parser.add_argument( |
| "--verbose-register-command-stream", action="store_true", help="Verbose register command stream" |
| ) |
| parser.add_argument("--verbose-operators", action="store_true", help="Verbose operator list") |
| |
| parser.add_argument( |
| "--show-minimum-possible-allocation", action="store_true", help="Show the minimum possible allocation" |
| ) |
| parser.add_argument( |
| "--show-cpu-operations", action="store_true", help="Show the operations that fall back to the CPU" |
| ) |
| parser.add_argument( |
| "--keep-scale-placement", action="store_true", help="Keep scale tensors memory placement during scheduling" |
| ) |
| parser.add_argument( |
| "--cascading", |
| type=ast.literal_eval, |
| default=True, |
| choices=[True, False], |
| help="Controls the packing of multiple passes into a cascade (default: %(default)s)", |
| ) |
| parser.add_argument("--force-block-config", type=str, default="", help="Force a specific block configuration HxWxC") |
| parser.add_argument("--timing", action="store_true", help="Time the compiler doing operations") |
| parser.add_argument( |
| "--accelerator-config", |
| type=str, |
| default="ethos-u55-256", |
| choices=list(architecture_features.Accelerator.member_list()), |
| help="Accelerator configuration to use (default: %(default)s)", |
| ) |
| parser.add_argument( |
| "--system-config", |
| type=str, |
| default="internal-default", |
| help="System configuration to use (default: %(default)s)", |
| ) |
| parser.add_argument( |
| "--tensor-allocator", |
| default=TensorAllocator.Greedy, |
| type=lambda s: TensorAllocator[s], |
| choices=list(TensorAllocator), |
| help="Tensor Allocator algorithm (default: %(default)s)", |
| ) |
| parser.add_argument( |
| "--show-subgraph-io-summary", |
| action="store_true", |
| help="Shows a summary of all the subgraphs and their inputs and outputs", |
| ) |
| parser.add_argument( |
| "--ifm-streaming", |
| type=ast.literal_eval, |
| default=True, |
| choices=[True, False], |
| help="Controls scheduler IFM streaming search (default: %(default)s)", |
| ) |
| parser.add_argument( |
| "--block-config-limit", |
| type=int, |
| default=16, |
| help="Limit block config search space, use zero for unlimited (default: %(default)s)", |
| ) |
| parser.add_argument( |
| "--global-memory-clock-scale", |
| type=float, |
| default=1.0, |
| help=( |
| "Performs an additional scaling of the individual memory clock scales specified by the system config " |
| "(default: %(default)s)" |
| ), |
| ) |
| parser.add_argument( |
| "--pareto-metric", |
| default=ParetoMetric.BwCycMem, |
| type=lambda s: ParetoMetric[s], |
| choices=list(ParetoMetric), |
| help="Controls the calculation of the pareto metric (default: %(default)s)", |
| ) |
| parser.add_argument( |
| "--recursion-limit", |
| type=int, |
| default=10000, |
| help="Set the recursion depth limit, may result in RecursionError if too low (default: %(default)s)", |
| ) |
| parser.add_argument( |
| "--max-block-dependency", |
| type=int, |
| default=architecture_features.ArchitectureFeatures.MAX_BLOCKDEP, |
| choices=range(0, architecture_features.ArchitectureFeatures.MAX_BLOCKDEP + 1), |
| help=( |
| "Set the maximum value that can be used for the block dependency between npu kernel operations " |
| "(default: %(default)s)" |
| ), |
| ) |
| parser.add_argument( |
| "--nhcwb16-between-cascaded-passes", |
| type=ast.literal_eval, |
| default=True, |
| choices=[True, False], |
| help="Control if NHCWB16 or NHWC should be used in between cascaded passes (default: %(default)s)", |
| ) |
| parser.add_argument( |
| "--weight-estimation-scaling", |
| type=float, |
| default=1.0, |
| help=("Performs an additional scaling of weight compression scale estimate (default: %(default)s)"), |
| ) |
| parser.add_argument( |
| "--allocation-alignment", |
| type=int, |
| default=Tensor.AllocationQuantum, |
| help=("Controls the allocation byte alignment of cpu tensors (default: %(default)s)"), |
| ) |
| args = parser.parse_args(args=args) |
| |
| # Read configuration file |
| config_file = args.config |
| config = None |
| if config_file is not None: |
| with open(config_file) as f: |
| config = configparser.ConfigParser() |
| config.read_file(f) |
| |
| # Generate the supported ops report and exit |
| if args.supported_ops_report: |
| generate_supported_ops() |
| return 0 |
| |
| if args.network is None: |
| parser.error("the following argument is required: NETWORK") |
| |
| sys.setrecursionlimit(args.recursion_limit) |
| |
| if args.force_block_config: |
| force_block_config = architecture_features.Block.from_string(args.force_block_config) |
| else: |
| force_block_config = None |
| |
| alignment = args.allocation_alignment |
| if alignment < 16: |
| parser.error("the following argument needs to be greater or equal to 16: ALLOCATION_ALIGNMENT") |
| if alignment & (alignment - 1) != 0: |
| parser.error("the following argument needs to be a power of 2: ALLOCATION_ALIGNMENT") |
| |
| arch = architecture_features.ArchitectureFeatures( |
| vela_config=config, |
| system_config=args.system_config, |
| accelerator_config=args.accelerator_config, |
| override_block_config=force_block_config, |
| block_config_limit=args.block_config_limit, |
| global_memory_clock_scale=args.global_memory_clock_scale, |
| max_blockdep=args.max_block_dependency, |
| weight_estimation_scaling=args.weight_estimation_scaling, |
| ) |
| |
| compiler_options = compiler_driver.CompilerOptions( |
| verbose_graph=args.verbose_graph, |
| verbose_quantization=args.verbose_quantization, |
| verbose_packing=args.verbose_packing, |
| verbose_tensor_purpose=args.verbose_tensor_purpose, |
| verbose_tensor_format=args.verbose_tensor_format, |
| verbose_allocation=args.verbose_allocation, |
| verbose_high_level_command_stream=args.verbose_high_level_command_stream, |
| verbose_register_command_stream=args.verbose_register_command_stream, |
| verbose_operators=args.verbose_operators, |
| show_minimum_possible_allocation=args.show_minimum_possible_allocation, |
| show_cpu_operations=args.show_cpu_operations, |
| tensor_allocator=args.tensor_allocator, |
| timing=args.timing, |
| output_dir=args.output_dir, |
| allocation_alignment=alignment, |
| ) |
| |
| scheduler_options = scheduler.SchedulerOptions( |
| use_cascading=args.cascading, |
| verbose_schedule=args.verbose_schedule, |
| verbose_pareto_frontier_schedules=args.verbose_pareto_frontier_schedules, |
| use_ifm_streaming=args.ifm_streaming, |
| pareto_metric=args.pareto_metric, |
| use_nhcwb16_between_cascaded_passes=args.nhcwb16_between_cascaded_passes, |
| keep_scale_placement=args.keep_scale_placement, |
| ) |
| |
| model_reader_options = model_reader.ModelReaderOptions() |
| |
| nng = process(args.network, args.enable_debug_db, arch, model_reader_options, compiler_options, scheduler_options) |
| |
| if args.show_subgraph_io_summary: |
| print_subgraph_io_summary(nng) |
| |
| return 0 |