(self, kernels_size=None, outputs=None)
| 39 | outputs: list, the output channels of each conv2d layer |
| 40 | """ |
| 41 | def __init__(self, kernels_size=None, outputs=None): |
| 42 | super(FormantLayer, self).__init__() |
| 43 | |
| 44 | if kernels_size is None: |
| 45 | kernels_size = [[3, 1], [3, 1], [3, 1], [3, 1], [2, 1]] |
| 46 | if outputs is None: |
| 47 | outputs = [72, 108, 162, 243, 256] |
| 48 | |
| 49 | self.kernels_size = kernels_size |
| 50 | self.outputs = outputs |
| 51 | |
| 52 | self.formant_layers = models.Sequential() |
| 53 | for i in range(len(self.kernels_size)): |
| 54 | self.formant_layers.add(conv2d_layer(filters=self.outputs[i], |
| 55 | kernel_size=self.kernels_size[i], |
| 56 | strides=[2, 1])) |
| 57 | |
| 58 | def call(self, x): |
| 59 | x = self.formant_layers(x) |
nothing calls this directly
no test coverage detected