<commit_before>from __future__ import division
from __future__ import print_function

import argparse
from datetime import datetime
import json
import os

import librosa
import numpy as np
import tensorflow as tf
import midi

from wavenet import WaveNetModel, mu_law_decode, mu_law_encode, audio_reader

SAMPLES = 16000
TEMPERATURE = 1.0
LOGDIR = './logdir'
WAVENET_PARAMS = './wavenet_params.json'
SAVE_EVERY = None
SILENCE_THRESHOLD = 0.1


def get_args():

	def _ensure_positive_float(f):
		"""Ensure argument is a positive float."""
		if float(f) < 0:
			raise argparse.ArgumentTypeError(
					'Argument must be greater than zero')
		return float(f)

	parser = argparse.ArgumentParser(description = 'WaveNet generation script')

	parser.add_argument('--checkpoint',
		type = str,
		help = 'Which model checkpoint to generate from')

	parser.add_argument('--samples',
		type = int,
		default = SAMPLES,
		help = 'How many waveform samples to generate')
	
	parser.add_argument('--temperature',
		type = _ensure_positive_float,
		default = TEMPERATURE,
		help = 'Sampling temperature')
	
	parser.add_argument('--logdir',
		type = str,
		default = LOGDIR,
		help = 'Directory in which to store the logging information for TensorBoard.')
	
	parser.add_argument('--wavenet-params',
		type = str,
		default = WAVENET_PARAMS,
		help = 'JSON file with the network parameters')
	
	parser.add_argument('--wav-out-path',
		type = str,
		default = None,
		help = 'Path to output wav file')
	
	parser.add_argument('--save-every',
		type = int,
		default = SAVE_EVERY,
		help = 'How many samples before saving in-progress wav')
	
	parser.add_argument('--fast-generation',
		type = bool,
		default = True,
		help = 'Use fast generation')
	
	parser.add_argument('--wav-seed',
		type = str,
		default = None,
		help = 'The wav file to start generation from')
	
	# GC params
	parser.add_argument('--gc-channels',
		type = int,
		default = None,
		help = 'Number of global condition channels. Default: None. Expecting: int')

	parser.add_argument('--gc-cardinality',
		type = int,
		default = None,
		help = 'Number of categories upon which we globally condition.')
	
	parser.add_argument('--gc-id',
		type = int,
		default = None,
		help = 'ID of category to generate, if globally conditioned.')

	# LC params
	parser.add_argument('--initial-lc-channels',
		type = int,
		default = None,
		help = "Number of inital local conditioning channels output by the upsampler. Default: None. Expecting: int")

	parser.add_argument('--lc-channels',
		type = int,
		default = None,
		help = "Number of local conditioning channels used by the network. Default: None. Expecting: int")

	parser.add_argument('--lc-fileformat',
		type = str,
		default = None,
		help = "Extension of files being used for local conditioning. Default: None. Expecting: string")

	parser.add_argument('--lc-filepath',
	    type = str,
	    default = None,
	    help = "Path to the file to be used for local condition based generation. Default: None. Expecting: string.")

	parse.add_argument('--sample-rate',
		type = int,
		default = 16000,
		help = "Default sample rate of the wav file. Used for properly upsampling the LC file. Default: 16000. Expecting: int.")
	<commit_msg>Fixed typo in arg parser<commit_after>from __future__ import division
from __future__ import print_function

import argparse
from datetime import datetime
import json
import os

import librosa
import numpy as np
import tensorflow as tf
import midi

from wavenet import WaveNetModel, mu_law_decode, mu_law_encode, audio_reader

SAMPLES = 16000
TEMPERATURE = 1.0
LOGDIR = './logdir'
WAVENET_PARAMS = './wavenet_params.json'
SAVE_EVERY = None
SILENCE_THRESHOLD = 0.1


def get_args():

	def _ensure_positive_float(f):
		"""Ensure argument is a positive float."""
		if float(f) < 0:
			raise argparse.ArgumentTypeError(
					'Argument must be greater than zero')
		return float(f)

	parser = argparse.ArgumentParser(description = 'WaveNet generation script')

	parser.add_argument('--checkpoint',
		type = str,
		help = 'Which model checkpoint to generate from')

	parser.add_argument('--samples',
		type = int,
		default = SAMPLES,
		help = 'How many waveform samples to generate')
	
	parser.add_argument('--temperature',
		type = _ensure_positive_float,
		default = TEMPERATURE,
		help = 'Sampling temperature')
	
	parser.add_argument('--logdir',
		type = str,
		default = LOGDIR,
		help = 'Directory in which to store the logging information for TensorBoard.')
	
	parser.add_argument('--wavenet-params',
		type = str,
		default = WAVENET_PARAMS,
		help = 'JSON file with the network parameters')
	
	parser.add_argument('--wav-out-path',
		type = str,
		default = None,
		help = 'Path to output wav file')
	
	parser.add_argument('--save-every',
		type = int,
		default = SAVE_EVERY,
		help = 'How many samples before saving in-progress wav')
	
	parser.add_argument('--fast-generation',
		type = bool,
		default = True,
		help = 'Use fast generation')
	
	parser.add_argument('--wav-seed',
		type = str,
		default = None,
		help = 'The wav file to start generation from')
	
	# GC params
	parser.add_argument('--gc-channels',
		type = int,
		default = None,
		help = 'Number of global condition channels. Default: None. Expecting: int')

	parser.add_argument('--gc-cardinality',
		type = int,
		default = None,
		help = 'Number of categories upon which we globally condition.')
	
	parser.add_argument('--gc-id',
		type = int,
		default = None,
		help = 'ID of category to generate, if globally conditioned.')

	# LC params
	parser.add_argument('--initial-lc-channels',
		type = int,
		default = None,
		help = "Number of inital local conditioning channels output by the upsampler. Default: None. Expecting: int")

	parser.add_argument('--lc-channels',
		type = int,
		default = None,
		help = "Number of local conditioning channels used by the network. Default: None. Expecting: int")

	parser.add_argument('--lc-fileformat',
		type = str,
		default = None,
		help = "Extension of files being used for local conditioning. Default: None. Expecting: string")

	parser.add_argument('--lc-filepath',
	    type = str,
	    default = None,
	    help = "Path to the file to be used for local condition based generation. Default: None. Expecting: string.")

	parser.add_argument('--sample-rate',
		type = int,
		default = 16000,
		help = "Default sample rate of the wav file. Used for properly upsampling the LC file. Default: 16000. Expecting: int.")
	
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