



# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# 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
#
#     http://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.
import ast
import difflib
from collections.abc import Mapping
from typing import Any, Callable, Dict






class 				SCREAMING_SNAKE_CASE     (							lowerCamelCase__   ):
							pass



def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     str			,       _SCREAMING_SNAKE_CASE    :     Dict[str, Callable]			,       _SCREAMING_SNAKE_CASE    :     List[Any]=None			,       _SCREAMING_SNAKE_CASE    :     Tuple=False      ):
				"""simple docstring"""







				try:
								__a					       =						ast.parse(_SCREAMING_SNAKE_CASE      )
				except SyntaxError as e:
								print("""The code generated by the agent is not valid.\n"""			,       _SCREAMING_SNAKE_CASE      )
								return
				if state is None:
								__a					       =						{}
				__a					       =						None
				for idx, node in enumerate(expression.body      ):
								try:
												__a					       =						evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
								except InterpretorError as e:
												__a					       =						f"Evaluation of the code stopped at line {idx} before the end because of the following error"
												if chat_mode:
																msg += (
																    f". Copy paste the following error message and send it back to the agent:\nI get an error: '{e}'"
																)
												else:
																msg += f":\n{e}"
												print(_SCREAMING_SNAKE_CASE      )
												break
								if line_result is not None:
												__a					       =						line_result

				return result

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     ast.AST			,       _SCREAMING_SNAKE_CASE    :     Dict[str, Any]			,       _SCREAMING_SNAKE_CASE    :     Dict[str, Callable]      ):
				"""simple docstring"""







				if isinstance(_SCREAMING_SNAKE_CASE			,       ast.Assign      ):
								# Assignement -> we evaluate the assignement which should update the state
								# We return the variable assigned as it may be used to determine the final result.
								return evaluate_assign(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Call      ):
								# Function call -> we return the value of the function call
								return evaluate_call(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Constant      ):
								# Constant -> just return the value
								return expression.value
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Dict      ):
								# Dict -> evaluate all keys and values
								__a					       =						[evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ) for k in expression.keys]
								__a					       =						[evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ) for v in expression.values]
								return dict(zip(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Expr      ):
								# Expression -> evaluate the content
								return evaluate_ast(expression.value			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.For      ):
								# For loop -> execute the loop
								return evaluate_for(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.FormattedValue      ):
								# Formatted value (part of f-string) -> evaluate the content and return
								return evaluate_ast(expression.value			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.If      ):
								# If -> execute the right branch
								return evaluate_if(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				elif hasattr(_SCREAMING_SNAKE_CASE			,       """Index"""      ) and isinstance(_SCREAMING_SNAKE_CASE			,       ast.Index      ):
								return evaluate_ast(expression.value			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.JoinedStr      ):
								return "".join([str(evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )      ) for v in expression.values]      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.List      ):
								# List -> evaluate all elements
								return [evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ) for elt in expression.elts]
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Name      ):
								# Name -> pick up the value in the state
								return evaluate_name(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Subscript      ):
								# Subscript -> return the value of the indexing
								return evaluate_subscript(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				else:
								# For now we refuse anything else. Let's add things as we need them.
								raise InterpretorError(f"{expression.__class__.__name__} is not supported."      )

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     str			,       _SCREAMING_SNAKE_CASE    :     Any			,       _SCREAMING_SNAKE_CASE    :     int      ):
				"""simple docstring"""







				__a					       =						assign.targets
				__a					       =						evaluate_ast(assign.value			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )

				if len(_SCREAMING_SNAKE_CASE      ) == 1:
								__a					       =						result
				else:
								if len(_SCREAMING_SNAKE_CASE      ) != len(_SCREAMING_SNAKE_CASE      ):
												raise InterpretorError(f"Expected {len(_SCREAMING_SNAKE_CASE      )} values but got {len(_SCREAMING_SNAKE_CASE      )}."      )
								for var_name, r in zip(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ):
												__a					       =						r
				return result

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Optional[int]			,       _SCREAMING_SNAKE_CASE    :     Union[str, Any]			,       _SCREAMING_SNAKE_CASE    :     Optional[int]      ):
				"""simple docstring"""







				if not isinstance(call.func			,       ast.Name      ):
								raise InterpretorError(
								    f"It is not permitted to evaluate other functions than the provided tools (tried to execute {call.func} of "
								    f"type {type(call.func      )}."      )
				__a					       =						call.func.id
				if func_name not in tools:
								raise InterpretorError(
								    f"It is not permitted to evaluate other functions than the provided tools (tried to execute {call.func.id})."      )

				__a					       =						tools[func_name]
				# Todo deal with args
				__a					       =						[evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ) for arg in call.args]
				__a					       =						{keyword.arg: evaluate_ast(keyword.value			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ) for keyword in call.keywords}
				return func(*_SCREAMING_SNAKE_CASE			,       **_SCREAMING_SNAKE_CASE      )

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     List[Any]			,       _SCREAMING_SNAKE_CASE    :     Tuple			,       _SCREAMING_SNAKE_CASE    :     int      ):
				"""simple docstring"""







				__a					       =						evaluate_ast(subscript.slice			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				__a					       =						evaluate_ast(subscript.value			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				if isinstance(_SCREAMING_SNAKE_CASE			,       (list, tuple)      ):
								return value[int(_SCREAMING_SNAKE_CASE      )]
				if index in value:
								return value[index]
				if isinstance(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ) and isinstance(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ):
								__a					       =						difflib.get_close_matches(_SCREAMING_SNAKE_CASE			,       list(value.keys()      )      )
								if len(_SCREAMING_SNAKE_CASE      ) > 0:
												return value[close_matches[0]]

				raise InterpretorError(f"Could not index {value} with '{index}'."      )

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     List[str]			,       _SCREAMING_SNAKE_CASE    :     int			,       _SCREAMING_SNAKE_CASE    :     Optional[int]      ):
				"""simple docstring"""







				if name.id in state:
								return state[name.id]
				__a					       =						difflib.get_close_matches(name.id			,       list(state.keys()      )      )
				if len(_SCREAMING_SNAKE_CASE      ) > 0:
								return state[close_matches[0]]
				raise InterpretorError(f"The variable `{name.id}` is not defined."      )

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Dict			,       _SCREAMING_SNAKE_CASE    :     Dict			,       _SCREAMING_SNAKE_CASE    :     Optional[Any]      ):
				"""simple docstring"""







				if len(condition.ops      ) > 1:
								raise InterpretorError("""Cannot evaluate conditions with multiple operators"""      )

				__a					       =						evaluate_ast(condition.left			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				__a					       =						condition.ops[0]
				__a					       =						evaluate_ast(condition.comparators[0]			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )

				if isinstance(_SCREAMING_SNAKE_CASE			,       ast.Eq      ):
								return left == right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.NotEq      ):
								return left != right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Lt      ):
								return left < right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.LtE      ):
								return left <= right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Gt      ):
								return left > right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.GtE      ):
								return left >= right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.Is      ):
								return left is right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.IsNot      ):
								return left is not right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.In      ):
								return left in right
				elif isinstance(_SCREAMING_SNAKE_CASE			,       ast.NotIn      ):
								return left not in right
				else:
								raise InterpretorError(f"Operator not supported: {comparator}"      )

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Any			,       _SCREAMING_SNAKE_CASE    :     Optional[int]			,       _SCREAMING_SNAKE_CASE    :     str      ):
				"""simple docstring"""







				__a					       =						None
				if evaluate_condition(if_statement.test			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      ):
								for line in if_statement.body:
												__a					       =						evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
												if line_result is not None:
																__a					       =						line_result
				else:
								for line in if_statement.orelse:
												__a					       =						evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
												if line_result is not None:
																__a					       =						line_result
				return result

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     List[Any]			,       _SCREAMING_SNAKE_CASE    :     Optional[Any]			,       _SCREAMING_SNAKE_CASE    :     Union[str, Any]      ):
				"""simple docstring"""







				__a					       =						None
				__a					       =						evaluate_ast(for_loop.iter			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
				for counter in iterator:
								__a					       =						counter
								for expression in for_loop.body:
												__a					       =						evaluate_ast(_SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE			,       _SCREAMING_SNAKE_CASE      )
												if line_result is not None:
																__a					       =						line_result
				return result





import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter

from transformers import HfArgumentParser

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Dict=None			,       _SCREAMING_SNAKE_CASE    :     List[str]=None      ):
				"""simple docstring"""







				return field(default_factory=lambda: default			,       metadata=_SCREAMING_SNAKE_CASE      )






@dataclass
class 				SCREAMING_SNAKE_CASE     :
							__lowerCamelCase		:		str      =field(
							    metadata={'help': 'The csv file to plot.'}     , )
							__lowerCamelCase		:		bool      =field(
							    default=lowerCamelCase__     , metadata={'help': 'Whether to plot along batch size or sequence length. Defaults to sequence length.'}     , )
							__lowerCamelCase		:		bool      =field(
							    default=lowerCamelCase__     , metadata={'help': 'Whether the csv file has time results or memory results. Defaults to memory results.'}     , )
							__lowerCamelCase		:		bool      =field(
							    default=lowerCamelCase__     , metadata={'help': 'Disable logarithmic scale when plotting'}     , )
							__lowerCamelCase		:		bool      =field(
							    default=lowerCamelCase__     , metadata={
							        'help': 'Whether the csv file has training results or inference results. Defaults to inference results.'
							    }     , )
							__lowerCamelCase		:		Optional[str]      =field(
							    default=lowerCamelCase__     , metadata={'help': 'Filename under which the plot will be saved. If unused no plot is saved.'}     , )
							__lowerCamelCase		:		Optional[List[str]]      =list_field(
							    default=lowerCamelCase__     , metadata={'help': 'List of model names that are used instead of the ones in the csv file.'}   )



def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Any      ):
				"""simple docstring"""







				try:
								int(_SCREAMING_SNAKE_CASE      )
								return True
				except ValueError:
								return False

def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Tuple      ):
				"""simple docstring"""







				try:
								float(_SCREAMING_SNAKE_CASE      )
								return True
				except ValueError:
								return False






class 				SCREAMING_SNAKE_CASE     :





							def __init__(				self						:						Optional[int] ,			__lowercase						:						str		):

											'''simple docstring'''
											__a					       =						args
											__a					       =						defaultdict(lambda: {"bsz": [], "seq_len": [], "result": {}}		)

											with open(self.args.csv_file ,			newline=""""""		) as csv_file:
															__a					       =						csv.DictReader(__lowercase		)
															for row in reader:
																			__a					       =						row["""model"""]
																			self.result_dict[model_name]["bsz"].append(int(row["""batch_size"""]		)		)
																			self.result_dict[model_name]["seq_len"].append(int(row["""sequence_length"""]		)		)
																			if can_convert_to_int(row["""result"""]		):
																							# value is not None
																							__a					       =						int(row["""result"""]		)
																			elif can_convert_to_float(row["""result"""]		):
																							# value is not None
																							__a					       =						float(row["""result"""]		)







							def   UpperCamelCase_   (				self						:						List[Any]		):

											'''simple docstring'''
											__a       ,   __a					       =						plt.subplots()
											__a					       =						"""Time usage""" if self.args.is_time else """Memory usage"""
											__a					       =						title_str + """ for training""" if self.args.is_train else title_str + """ for inference"""

											if not self.args.no_log_scale:
															# set logarithm scales
															ax.set_xscale("""log"""		)
															ax.set_yscale("""log"""		)

											for axis in [ax.xaxis, ax.yaxis]:
															axis.set_major_formatter(ScalarFormatter()		)

											for model_name_idx, model_name in enumerate(self.result_dict.keys()		):
															__a					       =						sorted(set(self.result_dict[model_name]["""bsz"""]		)		)
															__a					       =						sorted(set(self.result_dict[model_name]["""seq_len"""]		)		)
															__a					       =						self.result_dict[model_name]["""result"""]

															((__a)       ,   (__a))					       =						(
															    (batch_sizes, sequence_lengths) if self.args.plot_along_batch else (sequence_lengths, batch_sizes)
															)

															__a					       =						(
															    model_name if self.args.short_model_names is None else self.args.short_model_names[model_name_idx]
															)

															for inner_loop_value in inner_loop_array:
																			if self.args.plot_along_batch:
																							__a					       =						np.asarray(
																							    [results[(x, inner_loop_value)] for x in x_axis_array if (x, inner_loop_value) in results] ,			dtype=__lowercase ,			)
																			else:
																							__a					       =						np.asarray(
																							    [results[(inner_loop_value, x)] for x in x_axis_array if (inner_loop_value, x) in results] ,			dtype=np.floataa ,			)

																			((__a)       ,   (__a))					       =						(
																			    ("""batch_size""", """len""") if self.args.plot_along_batch else ("""in #tokens""", """bsz""")
																			)

																			__a					       =						np.asarray(__lowercase ,			__lowercase		)[: len(__lowercase		)]
																			plt.scatter(
																			    __lowercase ,			__lowercase ,			label=F"{label_model_name} - {inner_loop_label}: {inner_loop_value}"		)
																			plt.plot(__lowercase ,			__lowercase ,			"""--"""		)

															title_str += F" {label_model_name} vs."

											__a					       =						title_str[:-4]
											__a					       =						"""Time in s""" if self.args.is_time else """Memory in MB"""

											# plot
											plt.title(__lowercase		)
											plt.xlabel(__lowercase		)
											plt.ylabel(__lowercase		)
											plt.legend()

											if self.args.figure_png_file is not None:
															plt.savefig(self.args.figure_png_file		)
											else:
															plt.show()



def 					lowerCAmelCase__  (							):
				"""simple docstring"""







				__a					       =						HfArgumentParser(_SCREAMING_SNAKE_CASE      )
				__a					       =						parser.parse_args_into_dataclasses()[0]
				__a					       =						Plot(args=_SCREAMING_SNAKE_CASE      )
				plot.plot()


if __name__ == "__main__":
						main()
