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https://github.com/nod-ai/SHARK-Studio.git
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caf6cc5d8f
* Switch most compile flows to use ireec.compile_file. * re-add input type to compile_str path. * Check if mlir_module exists before checking if it's a path or pyobject. * Fix some save_dir cases
122 lines
4.0 KiB
Python
122 lines
4.0 KiB
Python
# Copyright 2020 The Nod Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from shark.iree_utils.compile_utils import (
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get_iree_compiled_module,
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get_results,
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export_iree_module_to_vmfb,
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load_flatbuffer,
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)
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from shark.iree_utils._common import check_device_drivers, device_driver_info
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from shark.parser import shark_args
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import os
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import sys
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# supported dialects by the shark-runtime.
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supported_dialects = {
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"linalg",
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"auto",
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"stablehlo",
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"tosa",
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"tf-lite",
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"tm_tensor",
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}
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class SharkRunner:
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"""
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Base class for SharkInference and SharkTrainer
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used to execute an mlir_module.
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...
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Attributes
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----------
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mlir_module : str
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mlir_module path, string, or bytecode.
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device : str
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device to execute the mlir_module on.
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currently supports cpu, cuda, vulkan, and metal backends.
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mlir_dialect: str
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The dialect in which the given mlir_module is in.
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Refer to {https://mlir.llvm.org/docs/Dialects/}
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Methods
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-------
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run(function_name, inputs=None):
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Runs the function with `function_name` within the mlir_module along
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with the given inputs, if the inputs are not given it autogenerates the
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inputs. Also, the inputs should be a numpy array.
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input_info():
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Gives the information about the inputs required by the `function_name`.
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This can be expensive as it does string matching to do so.
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"""
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def __init__(
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self,
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mlir_module: bytes = None,
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device: str = "none",
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mlir_dialect: str = "linalg",
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extra_args: list = [],
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compile_vmfb: bool = True,
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device_idx: int = None,
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):
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self.mlir_module = mlir_module
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if self.mlir_module is not None:
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if not os.path.isfile(mlir_module):
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print(
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"Warning: Initializing SharkRunner with a mlir string/bytecode object will duplicate the model in RAM at compile time. To avoid this, initialize SharkInference with a path to a MLIR module on your hard disk instead."
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)
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self.compile_str = True
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else:
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self.compile_str = False
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self.device = shark_args.device if device == "none" else device
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self.mlir_dialect = mlir_dialect
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self.extra_args = extra_args
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self.device_idx = device_idx
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if check_device_drivers(self.device):
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print(device_driver_info(self.device))
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sys.exit(1)
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if compile_vmfb == True:
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# Compile the module to get the .vmfb.
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params = get_iree_compiled_module(
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self.mlir_module,
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self.device,
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self.mlir_dialect,
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extra_args=self.extra_args,
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device_idx=self.device_idx,
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compile_str=self.compile_str,
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)
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self.iree_compilation_module = params["vmfb"]
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self.iree_config = params["config"]
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self.temp_file_to_unlink = params["temp_file_to_unlink"]
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del params
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def run(self, function_name, inputs: tuple, send_to_host=False):
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return get_results(
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self.iree_compilation_module,
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function_name,
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inputs,
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self.iree_config,
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self.mlir_dialect,
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send_to_host,
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)
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# Get all function names defined within the compiled module.
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def get_functions_in_module(self):
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return self.iree_compilation_module._vm_module.function_names
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