



import re
import time
from typing import Optional

import IPython.display as disp

from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length






def        A       (      _lowerCamelCase						):





							'''simple docstring'''




							_lowerCAmelCase  :							Tuple				     =					int(_lowerCamelCase						)
							_lowerCAmelCase     ,					_lowerCAmelCase     ,					_lowerCAmelCase  :							Optional[Any]				     =					t // 3_600, (t // 60) % 60, t % 60
							return F"{h}:{m:02d}:{s:02d}" if h != 0 else F"{m:02d}:{s:02d}"






def        A       (      _lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase=300						):





							'''simple docstring'''




							return F"\n    <div>\n      {prefix}\n      <progress value='{value}' max='{total}' style='width:{width}px; height:20px; vertical-align: middle;'></progress>\n      {label}\n    </div>\n    "






def        A       (      _lowerCamelCase						):





							'''simple docstring'''




							_lowerCAmelCase  :							str				     =					"<table border=\"1\" class=\"dataframe\">\n"
							html_code += """  <thead>\n <tr style="text-align: left;">\n"""
							for i in items[0]:
														html_code += F"      <th>{i}</th>\n"
							html_code += "    </tr>\n  </thead>\n  <tbody>\n"
							for line in items[1:]:
														html_code += "    <tr>\n"
														for elt in line:
																					_lowerCAmelCase  :							Optional[int]				     =					F"{elt:.6f}" if isinstance(_lowerCamelCase       ,				_lowerCamelCase						) else str(_lowerCamelCase						)
																					html_code += F"      <td>{elt}</td>\n"
														html_code += "    </tr>\n"
							html_code += "  </tbody>\n</table><p>"
							return html_code



class 						UpperCAmelCase_					:
							lowerCamelCase__         =	5
							lowerCamelCase__         =	0.2







							def __init__(     self,    __a,    __a = None,    __a = True,    __a = None,    __a = 300,    ):

														'''simple docstring'''

														_lowerCAmelCase  :							List[Any]				     =					total
														_lowerCAmelCase  :							Any				     =					"" if prefix is None else prefix
														_lowerCAmelCase  :							str				     =					leave
														_lowerCAmelCase  :							Optional[Any]				     =					parent
														_lowerCAmelCase  :							Optional[int]				     =					width
														_lowerCAmelCase  :							Tuple				     =					None
														_lowerCAmelCase  :							Dict				     =					None
														_lowerCAmelCase  :							Tuple				     =					None







							def      snake_case__   (     self,    __a,    __a = False,    __a = None):

														'''simple docstring'''

														_lowerCAmelCase  :							List[Any]				     =					value
														if comment is not None:
																					_lowerCAmelCase  :							Union[str, Any]				     =					comment
														if self.last_value is None:
																					_lowerCAmelCase  :							Optional[int]				     =					time.time()
																					_lowerCAmelCase  :							Any				     =					value
																					_lowerCAmelCase  :							Optional[int]				     =					None
																					_lowerCAmelCase  :							Dict				     =					self.warmup
																					_lowerCAmelCase  :							Union[str, Any]				     =					1
																					self.update_bar(__a)
														elif value <= self.last_value and not force_update:
																					return
														elif force_update or self.first_calls > 0 or value >= min(self.last_value + self.wait_for,    self.total):
																					if self.first_calls > 0:
																												self.first_calls -= 1
																					_lowerCAmelCase  :							Dict				     =					time.time()
																					_lowerCAmelCase  :							str				     =					current_time - self.start_time
																					# We could have value = self.start_value if the update is called twixe with the same start value.
																					if value > self.start_value:
																												_lowerCAmelCase  :							List[str]				     =					self.elapsed_time / (value - self.start_value)
																					else:
																												_lowerCAmelCase  :							Optional[Any]				     =					None
																					if value >= self.total:
																												_lowerCAmelCase  :							Optional[int]				     =					self.total
																												_lowerCAmelCase  :							int				     =					None
																												if not self.leave:
																																			self.close()
																					elif self.average_time_per_item is not None:
																												_lowerCAmelCase  :							Tuple				     =					self.average_time_per_item * (self.total - value)
																					self.update_bar(__a)
																					_lowerCAmelCase  :							str				     =					value
																					_lowerCAmelCase  :							List[Any]				     =					current_time
																					if self.average_time_per_item is None:
																												_lowerCAmelCase  :							List[str]				     =					1
																					else:
																												_lowerCAmelCase  :							Tuple				     =					max(int(self.update_every / self.average_time_per_item),    1)







							def      snake_case__   (     self,    __a,    __a=None):

														'''simple docstring'''

														_lowerCAmelCase  :							Union[str, Any]				     =					" " * (len(str(self.total)) - len(str(__a))) + str(__a)
														if self.elapsed_time is None:
																					_lowerCAmelCase  :							Optional[int]				     =					f"[{spaced_value}/{self.total} : < :"
														elif self.predicted_remaining is None:
																					_lowerCAmelCase  :							Optional[int]				     =					f"[{spaced_value}/{self.total} {format_time(self.elapsed_time)}"
														else:
																					_lowerCAmelCase  :							List[str]				     =					(
																					    f"[{spaced_value}/{self.total} {format_time(self.elapsed_time)} <"
																					    f" {format_time(self.predicted_remaining)}"
																					)
																					self.label += f", {1/self.average_time_per_item:.2f} it/s"
														self.label += "]" if self.comment is None or len(self.comment) == 0 else f", {self.comment}]"
														self.display()







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Union[str, Any]				     =					html_progress_bar(self.value,    self.total,    self.prefix,    self.label,    self.width)
														if self.parent is not None:
																					# If this is a child bar, the parent will take care of the display.
																					self.parent.display()
																					return
														if self.output is None:
																					_lowerCAmelCase  :							List[str]				     =					disp.display(disp.HTML(self.html_code),    display_id=__a)
														else:
																					self.output.update(disp.HTML(self.html_code))







							def      snake_case__   (     self):

														'''simple docstring'''

														if self.parent is None and self.output is not None:
																					self.output.update(disp.HTML(""))



class 						UpperCAmelCase_					( a):







							def __init__(     self,    __a,    __a=None):

														'''simple docstring'''

														super().__init__(__a)
														_lowerCAmelCase  :							str				     =					None if column_names is None else [column_names]
														_lowerCAmelCase  :							List[Any]				     =					None







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Union[str, Any]				     =					html_progress_bar(self.value,    self.total,    self.prefix,    self.label,    self.width)
														if self.inner_table is not None:
																					self.html_code += text_to_html_table(self.inner_table)
														if self.child_bar is not None:
																					self.html_code += self.child_bar.html_code
														if self.output is None:
																					_lowerCAmelCase  :							Union[str, Any]				     =					disp.display(disp.HTML(self.html_code),    display_id=__a)
														else:
																					self.output.update(disp.HTML(self.html_code))







							def      snake_case__   (     self,    __a):

														'''simple docstring'''

														if self.inner_table is None:
																					_lowerCAmelCase  :							str				     =					[list(values.keys()), list(values.values())]
														else:
																					_lowerCAmelCase  :							List[Any]				     =					self.inner_table[0]
																					if len(self.inner_table) == 1:
																												# We give a chance to update the column names at the first iteration
																												for key in values.keys():
																																			if key not in columns:
																																										columns.append(__a)
																												_lowerCAmelCase  :							Optional[Any]				     =					columns
																					self.inner_table.append([values[c] for c in columns])







							def      snake_case__   (     self,    __a,    __a=None,    __a=300):

														'''simple docstring'''

														_lowerCAmelCase  :							Any				     =					NotebookProgressBar(__a,    prefix=__a,    parent=self,    width=__a)
														return self.child_bar







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[Any]				     =					None
														self.display()



class 						UpperCAmelCase_					( a):







							def __init__(     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Tuple				     =					None
														_lowerCAmelCase  :							List[Any]				     =					None
														_lowerCAmelCase  :							List[str]				     =					False







							def      snake_case__   (     self,    __a,    __a,    __a,    **__a):

														'''simple docstring'''

														_lowerCAmelCase  :							Tuple				     =					"Epoch" if args.evaluation_strategy == IntervalStrategy.EPOCH else "Step"
														_lowerCAmelCase  :							Optional[Any]				     =					0
														_lowerCAmelCase  :							Optional[Any]				     =					0
														_lowerCAmelCase  :							Union[str, Any]				     =					[self.first_column] + ["Training Loss"]
														if args.evaluation_strategy != IntervalStrategy.NO:
																					column_names.append("Validation Loss")
														_lowerCAmelCase  :							List[Any]				     =					NotebookTrainingTracker(state.max_steps,    __a)







							def      snake_case__   (     self,    __a,    __a,    __a,    **__a):

														'''simple docstring'''

														_lowerCAmelCase  :							str				     =					int(state.epoch) if int(state.epoch) == state.epoch else f"{state.epoch:.2f}"
														self.training_tracker.update(
														    state.global_step + 1,    comment=f"Epoch {epoch}/{state.num_train_epochs}",    force_update=self._force_next_update,    )
														_lowerCAmelCase  :							Tuple				     =					False







							def      snake_case__   (     self,    __a,    __a,    __a,    __a=None,    **__a):

														'''simple docstring'''

														if not has_length(__a):
																					return
														if self.prediction_bar is None:
																					if self.training_tracker is not None:
																												_lowerCAmelCase  :							Any				     =					self.training_tracker.add_child(len(__a))
																					else:
																												_lowerCAmelCase  :							Tuple				     =					NotebookProgressBar(len(__a))
																					self.prediction_bar.update(1)
														else:
																					self.prediction_bar.update(self.prediction_bar.value + 1)







							def      snake_case__   (     self,    __a,    __a,    __a,    **__a):

														'''simple docstring'''

														if self.prediction_bar is not None:
																					self.prediction_bar.close()
														_lowerCAmelCase  :							List[Any]				     =					None







							def      snake_case__   (     self,    __a,    __a,    __a,    __a=None,    **__a):

														'''simple docstring'''

														if args.evaluation_strategy == IntervalStrategy.NO and "loss" in logs:
																					_lowerCAmelCase  :							Any				     =					{"Training Loss": logs["loss"]}
																					# First column is necessarily Step sine we're not in epoch eval strategy
																					_lowerCAmelCase  :							List[str]				     =					state.global_step
																					self.training_tracker.write_line(__a)







							def      snake_case__   (     self,    __a,    __a,    __a,    __a=None,    **__a):

														'''simple docstring'''

														if self.training_tracker is not None:
																					_lowerCAmelCase  :							Tuple				     =					{"Training Loss": "No log", "Validation Loss": "No log"}
																					for log in reversed(state.log_history):
																												if "loss" in log:
																																			_lowerCAmelCase  :							Tuple				     =					log["loss"]
																																			break

																					if self.first_column == "Epoch":
																												_lowerCAmelCase  :							int				     =					int(state.epoch)
																					else:
																												_lowerCAmelCase  :							Optional[Any]				     =					state.global_step
																					_lowerCAmelCase  :							Union[str, Any]				     =					"eval"
																					for k in metrics:
																												if k.endswith("_loss"):
																																			_lowerCAmelCase  :							Any				     =					re.sub(R"\_loss$",    "",    __a)
																					_lowerCAmelCase  :							Optional[Any]				     =					metrics.pop("total_flos",    __a)
																					_lowerCAmelCase  :							str				     =					metrics.pop("epoch",    __a)
																					_lowerCAmelCase  :							Any				     =					metrics.pop(f"{metric_key_prefix}_runtime",    __a)
																					_lowerCAmelCase  :							Union[str, Any]				     =					metrics.pop(f"{metric_key_prefix}_samples_per_second",    __a)
																					_lowerCAmelCase  :							List[str]				     =					metrics.pop(f"{metric_key_prefix}_steps_per_second",    __a)
																					_lowerCAmelCase  :							List[str]				     =					metrics.pop(f"{metric_key_prefix}_jit_compilation_time",    __a)
																					for k, v in metrics.items():
																												if k == f"{metric_key_prefix}_loss":
																																			_lowerCAmelCase  :							List[Any]				     =					v
																												else:
																																			_lowerCAmelCase  :							str				     =					k.split("_")
																																			_lowerCAmelCase  :							int				     =					" ".join([part.capitalize() for part in splits[1:]])
																																			_lowerCAmelCase  :							List[str]				     =					v
																					self.training_tracker.write_line(__a)
																					self.training_tracker.remove_child()
																					_lowerCAmelCase  :							List[Any]				     =					None
																					# Evaluation takes a long time so we should force the next update.
																					_lowerCAmelCase  :							int				     =					True







							def      snake_case__   (     self,    __a,    __a,    __a,    **__a):

														'''simple docstring'''

														self.training_tracker.update(
														    state.global_step,    comment=f"Epoch {int(state.epoch)}/{state.num_train_epochs}",    force_update=__a)
														_lowerCAmelCase  :							Dict				     =					None





import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey






def        A       (      _lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase       ,				_lowerCamelCase						):





							'''simple docstring'''




							if (ksize % 2) == 0:
														_lowerCAmelCase  :							str				     =					ksize + 1
							_lowerCAmelCase  :							List[str]				     =					np.zeros((ksize, ksize)       ,				dtype=np.floataa						)

							# each value
							for y in range(_lowerCamelCase						):
														for x in range(_lowerCamelCase						):
																					# distance from center
																					_lowerCAmelCase  :							int				     =					x - ksize // 2
																					_lowerCAmelCase  :							Dict				     =					y - ksize // 2

																					# degree to radiant
																					_lowerCAmelCase  :							List[Any]				     =					theta / 180 * np.pi
																					_lowerCAmelCase  :							int				     =					np.cos(_theta						)
																					_lowerCAmelCase  :							Optional[int]				     =					np.sin(_theta						)

																					# get kernel x
																					_lowerCAmelCase  :							int				     =					cos_theta * px + sin_theta * py

																					# get kernel y
																					_lowerCAmelCase  :							str				     =					-sin_theta * px + cos_theta * py

																					# fill kernel
																					_lowerCAmelCase  :							Union[str, Any]				     =					np.exp(
																					    -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2)						) * np.cos(2 * np.pi * _x / lambd + psi						)

							return gabor


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						# read original image
						_snake_case	=						imread("../image_data/lena.jpg")
						# turn image in gray scale value
						_snake_case	=						cvtColor(img, COLOR_BGR2GRAY)

						# Apply multiple Kernel to detect edges
						_snake_case	=						np.zeros(gray.shape[:2])
						for theta in [0, 30, 60, 90, 120, 150]:
												_snake_case	=						gabor_filter_kernel(10, 8, theta, 10, 0, 0)
												out += filteraD(gray, CV_8UC3, kernel_aa)
						_snake_case	=						out / out.max() * 255
						_snake_case	=						out.astype(np.uinta)

						imshow("Original", gray)
						imshow("Gabor filter with 20x20 mask and 6 directions", out)

						waitKey(0)
