[New Sample] Add cv samples with argmax operators #278

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	import ast
	import json
	import importlib
	import inspect
	from dataclasses import dataclass, field
	from typing import Dict


	@dataclass
	class OpStat:
	op_name: str
	op_dtypes: dict[str, int] = field(default_factory=dict)
	count: int = 0

	def update(self, other):
	if isinstance(other, OpStat) and self.op_name == other.op_name:
	self.count += other.count
	for name, count in other.op_dtypes.items():
	self.op_dtypes[name] = self.op_dtypes.get(name, 0) + count


	@dataclass
	class ModelStats:
	model_path: str
	num_inputs: int = None
	num_params: int = None
	num_outputs: int = None
	num_ops: int = None
	model_size_in_billion: float = None
	input_dtypes: Dict[str, int] = field(default_factory=dict)
	param_dtypes: Dict[str, int] = field(default_factory=dict)
	input_shapes: Dict[str, list] = field(default_factory=dict)
	op_dtypes: Dict[str, int] = field(default_factory=dict)
	ops: Dict[str, int] = field(default_factory=dict)
	source: str = None
	heuristic_tag: str = None


	def print_model_stats(stats, log_prompt):
	assert isinstance(stats, ModelStats), f"{type(stats)=}"

	def print_with_log_prompt(key, value):
	print(
	f"{log_prompt} [ModelStats.{key}] model_path:{stats.model_path} {value}",
	flush=True,
	)

	print_with_log_prompt("num_inputs", stats.num_inputs)
	print_with_log_prompt("num_params", stats.num_params)
	print_with_log_prompt("num_outputs", stats.num_outputs)
	print_with_log_prompt("num_ops", stats.num_ops)
	print_with_log_prompt("model_size", f"{stats.model_size_in_billion}B")
	print_with_log_prompt("input_dtypes", json.dumps(stats.input_dtypes))
	print_with_log_prompt("param_dtypes", json.dumps(stats.param_dtypes))
	print_with_log_prompt("input_shapes", json.dumps(stats.input_shapes))
	print_with_log_prompt("op_dtypes", json.dumps(stats.op_dtypes))
	print_with_log_prompt("ops", json.dumps(stats.ops))
	print_with_log_prompt("source", stats.source)
	print_with_log_prompt("heuristic_tag", stats.heuristic_tag)


	def load_class_from_file(file_path, class_name):
	spec = importlib.util.spec_from_file_location("unnamed", file_path)
	unnamed = importlib.util.module_from_spec(spec)
	spec.loader.exec_module(unnamed)
	model_class = getattr(unnamed, class_name, None)
	return model_class


	def get_argument_name_and_types(model_class, func_name):
	argument_name2types = {}
	for name, func in inspect.getmembers(model_class, predicate=inspect.isfunction):
	if name == func_name:
	for arg_name, arg in inspect.signature(func).parameters.items():
	if arg_name != "self":
	argument_name2types[arg_name] = (
	None if arg.annotation is inspect._empty else arg.annotation
	)
	return argument_name2types


	def get_number_of_returns(file_path, class_name, func_name):
	source = None
	with open(f"{file_path}", "r") as f:
	source = f.read()

	tree = ast.parse(source)
	for node in tree.body:
	if isinstance(node, ast.ClassDef) and node.name == class_name:
	for f in node.body:
	if isinstance(f, ast.FunctionDef) and f.name == func_name:
	for stmt in ast.walk(f):
	if isinstance(stmt, ast.Return):
	if stmt.value is None:
	return 0
	elif isinstance(stmt.value, ast.Tuple):
	return len(stmt.value.elts)
	else:
	return 1
	return 0

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