| 98 | """ |
| 99 | |
| 100 | def __init__(self, rank, |
| 101 | filters, |
| 102 | kernel_size, |
| 103 | strides=1, |
| 104 | padding='valid', |
| 105 | data_format=None, |
| 106 | dilation_rate=1, |
| 107 | activation=None, |
| 108 | use_bias=True, |
| 109 | kernel_initializer='glorot_uniform', |
| 110 | bias_initializer='zeros', |
| 111 | kernel_regularizer=None, |
| 112 | bias_regularizer=None, |
| 113 | activity_regularizer=None, |
| 114 | kernel_constraint=None, |
| 115 | bias_constraint=None, |
| 116 | trainable=True, |
| 117 | name=None, |
| 118 | fused=False, |
| 119 | **kwargs): |
| 120 | super(Conv, self).__init__( |
| 121 | trainable=trainable, |
| 122 | name=name, |
| 123 | activity_regularizer=regularizers.get(activity_regularizer), |
| 124 | **kwargs) |
| 125 | self.rank = rank |
| 126 | self.filters = filters |
| 127 | self.kernel_size = conv_utils.normalize_tuple( |
| 128 | kernel_size, rank, 'kernel_size') |
| 129 | self.strides = conv_utils.normalize_tuple(strides, rank, 'strides') |
| 130 | self.padding = conv_utils.normalize_padding(padding) |
| 131 | if (self.padding == 'causal' and not isinstance(self, |
| 132 | (Conv1D, SeparableConv1D))): |
| 133 | raise ValueError('Causal padding is only supported for `Conv1D`' |
| 134 | 'and ``SeparableConv1D`.') |
| 135 | self.data_format = conv_utils.normalize_data_format(data_format) |
| 136 | self.dilation_rate = conv_utils.normalize_tuple( |
| 137 | dilation_rate, rank, 'dilation_rate') |
| 138 | self.activation = activations.get(activation) |
| 139 | self.use_bias = use_bias |
| 140 | self.kernel_initializer = initializers.get(kernel_initializer) |
| 141 | self.bias_initializer = initializers.get(bias_initializer) |
| 142 | self.kernel_regularizer = regularizers.get(kernel_regularizer) |
| 143 | self.bias_regularizer = regularizers.get(bias_regularizer) |
| 144 | self.kernel_constraint = constraints.get(kernel_constraint) |
| 145 | self.bias_constraint = constraints.get(bias_constraint) |
| 146 | self.input_spec = InputSpec(ndim=self.rank + 2) |
| 147 | self.fused = fused |
| 148 | |
| 149 | def build(self, input_shape): |
| 150 | input_shape = tensor_shape.TensorShape(input_shape) |