marcoleewow

marcoleewow

import os
import numpy as np

import coremltools
from coremltools.models.neural_network import flexible_shape_utils

import torch
from torch import nn

import onnx

marcoleewow

import editdistance
  
  
def cer(y_true: str, y_pred: str) -> float:
    assert isinstance(y_true, str) and isinstance(y_pred, str)
    n_err = editdistance.eval(y_true.rstrip(), y_pred.rstrip())
    return n_err / len(y_true)

  
def wer(transcript: str, reference: str) -> float:

marcoleewow

import torch
from torch import nn
import torch.nn.functional as F
import os
import onnx
from onnx_coreml import convert
import pytest
from coremltools.proto import NeuralNetwork_pb2 #type: ignore

"""

marcoleewow

Keybase proof

I hereby claim:

• I am marcoleewow on github.
• I am marcoleewow (https://keybase.io/marcoleewow) on keybase.
• I have a public key ASA5wRJ5pC3LsccRazSVrRDLjSgWk7bsSAGb09DGjtRDEQo

To claim this, I am signing this object:

marcoleewow

import numpy as np
import tensorflow as tf

def CTCLossExactPathTest():
  
    BIG_NEG_NUMBER = -100
    logit = np.array([[BIG_NEG_NUMBER, 0., BIG_NEG_NUMBER, BIG_NEG_NUMBER],
                      [0., BIG_NEG_NUMBER, BIG_NEG_NUMBER, BIG_NEG_NUMBER],
                      [BIG_NEG_NUMBER, BIG_NEG_NUMBER, 0., BIG_NEG_NUMBER]])
    """

marcoleewow

import numpy as np
import tensorflow as tf

def CTCLossSimpleTest():
    """
    Alex Graves Paper example:
    #      a    -
    P = [[0.3, 0.7], # t = 0
         [0.4, 0.6]] # t = 1

marcoleewow

import numpy as np
from keras import backend as K
from keras.layers import *

from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential, Model
from keras.optimizers import SGD, Adam

np.random.seed(1337)  # for reproducibility