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Python core.Layer方法代码示例

本文整理汇总了Python中keras.layers.core.Layer方法的典型用法代码示例。如果您正苦于以下问题:Python core.Layer方法的具体用法?Python core.Layer怎么用?Python core.Layer使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在keras.layers.core的用法示例。


在下文中一共展示了core.Layer方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: test_input_output

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def test_input_output(self):
        nb_samples = 10
        input_dim = 5
        layer = core.Layer()

        # As long as there is no input, an error should be raised.
        for train in [True, False]:
            self.assertRaises(AttributeError, layer.get_input, train)
            self.assertRaises(AttributeError, layer.get_output, train)

        # Once an input is provided, it should be reachable through the
        # appropriate getters
        input = np.ones((nb_samples, input_dim))
        layer.input = theano.shared(value=input)
        for train in [True, False]:
            assert_allclose(layer.get_input(train).eval(), input)
            assert_allclose(layer.get_output(train).eval(), input) 
开发者ID:lllcho,项目名称:CAPTCHA-breaking,代码行数:19,代码来源:test_core.py

示例2: test_connections

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def test_connections(self):
        nb_samples = 10
        input_dim = 5
        layer1 = core.Layer()
        layer2 = core.Layer()

        input = np.ones((nb_samples, input_dim))
        layer1.input = theano.shared(value=input)

        # As long as there is no previous layer, an error should be raised.
        for train in [True, False]:
            self.assertRaises(AttributeError, layer2.get_input, train)

        # After connecting, input of layer1 should be passed through
        layer2.set_previous(layer1)
        for train in [True, False]:
            assert_allclose(layer2.get_input(train).eval(), input)
            assert_allclose(layer2.get_output(train).eval(), input) 
开发者ID:lllcho,项目名称:CAPTCHA-breaking,代码行数:20,代码来源:test_core.py

示例3: emit_Slice

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def emit_Slice(self, IR_node, in_scope=False):
        # It arouses some problems:
        # it can be implemented by Lambda Layer
        # https://github.com/keras-team/keras/issues/890

        self.used_layers.add(IR_node.type)

        extra_str = ""
        if IR_node.get_attr('strides'):
            extra_str += "strides={}".format(IR_node.get_attr('strides'))
        if IR_node.get_attr('begin_mask'):
            extra_str += ", begin_mask={}".format(IR_node.get_attr('begin_mask'))
        if IR_node.get_attr('end_mask'):
            extra_str += ", end_mask={}".format(IR_node.get_attr('end_mask'))
        if IR_node.get_attr('shrink_axis_mask'):
            extra_str += ", shrink_axis_mask={}".format(IR_node.get_attr('shrink_axis_mask'))

        code = "{:<15} = __slice({}, {}, {}, {})".format(
            IR_node.variable_name,
            self.parent_variable_name(IR_node),
            IR_node.get_attr('starts'),
            IR_node.get_attr('ends'),
            extra_str)
        return code 
开发者ID:microsoft,项目名称:MMdnn,代码行数:26,代码来源:keras2_emitter.py

示例4: _emit_h_zero

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def _emit_h_zero(self, IR_node):
        if not self.layers_codes.get(IR_node.pattern, None):
            class_code = '''
class my_h_zero(keras.layers.Layer):
    def __init__(self, **kwargs):
        super(my_h_zero, self).__init__(**kwargs)
    
    def call(self, dummy):
        {:<15} = K.constant(np.full((1, {}), {}))

        return {}
            '''.format(IR_node.variable_name,
            IR_node.get_attr('fill_size'),
            IR_node.get_attr('fill_value'),
            IR_node.variable_name)
            self.layers_codes[IR_node.pattern] = class_code

        code = "{:<15} = my_h_zero()({})".format(IR_node.variable_name, self.parent_variable_name(IR_node))

        return code 
开发者ID:microsoft,项目名称:MMdnn,代码行数:22,代码来源:keras2_emitter.py

示例5: _layer_Affine

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def _layer_Affine(self):
        self.add_body(0, '''
from keras.engine import Layer, InputSpec
from keras import initializers
from keras  import backend as K

class Affine(Layer):
    def __init__(self, scale, bias=None, **kwargs):
        super(Affine, self).__init__(**kwargs)
        self.gamma = scale
        self.beta = bias

    def call(self, inputs, training=None):
        input_shape = K.int_shape(inputs)
        # Prepare broadcasting shape.
        return self.gamma * inputs + self.beta

    def compute_output_shape(self, input_shape):
        return input_shape
        ''') 
开发者ID:microsoft,项目名称:MMdnn,代码行数:22,代码来源:keras2_emitter.py

示例6: _layer_Shape

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def _layer_Shape(self):
        self.add_body(0, '''
def __shape(input):
    return Lambda(lambda x: tf.shape(x))(input)
        ''')

#     def _layer_Constant(self):
#         self.add_body(0, '''
# class my_constant(keras.layers.Layer):
#     def __init__(self, value, **kwargs):
#         super(my_constant, self).__init__(**kwargs)
#         self._value = value
#     # the input is dummy, just for creating keras graph.
#     def call(self, dummy):
#         res = K.constant(self._value)
#         self.output_shapes = K.int_shape(res)
#         return res
    
#     def compute_output_shape(self, input_shape):
#         return self.output_shapes
# ''') 
开发者ID:microsoft,项目名称:MMdnn,代码行数:23,代码来源:keras2_emitter.py

示例7: test_base

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def test_base(self):
        layer = core.Layer()
        self._runner(layer) 
开发者ID:lllcho,项目名称:CAPTCHA-breaking,代码行数:5,代码来源:test_core.py

示例8: test_merge

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def test_merge(self):
        layer_1 = core.Layer()
        layer_2 = core.Layer()
        layer = core.Merge([layer_1, layer_2])
        self._runner(layer) 
开发者ID:lllcho,项目名称:CAPTCHA-breaking,代码行数:7,代码来源:test_core.py

示例9: test_autoencoder

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def test_autoencoder(self):
        layer_1 = core.Layer()
        layer_2 = core.Layer()

        layer = core.AutoEncoder(layer_1, layer_2)
        self._runner(layer) 
开发者ID:lllcho,项目名称:CAPTCHA-breaking,代码行数:8,代码来源:test_core.py

示例10: _layer_LRN

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def _layer_LRN(self):
        self.add_body(0, '''
from keras.layers.core import Layer
class LRN(Layer):

    def __init__(self, size=5, alpha=0.0005, beta=0.75, k=2, **kwargs):
        self.n = size
        self.alpha = alpha
        self.beta = beta
        self.k = k
        super(LRN, self).__init__(**kwargs)

    def build(self, input_shape):
        self.shape = input_shape
        super(LRN, self).build(input_shape)

    def call(self, x, mask=None):
        half_n = int(self.n/2)
        squared = K.square(x)
        scale = self.k
        norm_alpha = self.alpha / self.n
        if (K.image_data_format() == 'channels_first'):
            b, f, r, c = self.shape
            squared = K.expand_dims(squared, 0)
            squared = K.spatial_3d_padding(squared, padding=((half_n, half_n), (0, 0), (0,0)))
            squared = K.squeeze(squared, 0)
            for i in range(self.n):
                scale += norm_alpha * squared[:, i:i+f, :, :]
        else:
            b, r, c, f = self.shape
            squared = K.expand_dims(squared, -1)
            squared = K.spatial_3d_padding(squared, padding=((0, 0), (0,0), (half_n, half_n)))
            squared = K.squeeze(squared, -1)
            for i in range(self.n):
                scale += norm_alpha * squared[:, :, :, i:i+f]

        scale = K.pow(scale, self.beta)
        return x / scale

    def compute_output_shape(self, input_shape):
        return input_shape''') 
开发者ID:microsoft,项目名称:MMdnn,代码行数:43,代码来源:keras2_emitter.py

示例11: _layer_Mul

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def _layer_Mul(self):
        self.add_body(0, '''
class my_mul(keras.layers.Layer):
    def __init__(self, **kwargs):
        super(my_mul, self).__init__(**kwargs)
    def call(self, inputs):
        res = inputs[0] * inputs[1]
        self.output_shapes = K.int_shape(res)
        return res
    
    def compute_output_shape(self, input_shape):
        return self.output_shapes
''') 
开发者ID:microsoft,项目名称:MMdnn,代码行数:15,代码来源:keras2_emitter.py

示例12: _layer_Add

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def _layer_Add(self):
        self.add_body(0, '''
class my_add(keras.layers.Layer):
    def __init__(self, **kwargs):
        super(my_add, self).__init__(**kwargs)
    def call(self, inputs):
        res = inputs[0] + inputs[1]
        self.output_shapes = K.int_shape(res)
        return res
    
    def compute_output_shape(self, input_shape):
        return self.output_shapes
''') 
开发者ID:microsoft,项目名称:MMdnn,代码行数:15,代码来源:keras2_emitter.py

示例13: _layer_Sub

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def _layer_Sub(self):
        self.add_body(0, '''
class my_sub(keras.layers.Layer):
    def __init__(self, **kwargs):
        super(my_sub, self).__init__(**kwargs)
    def call(self, inputs):
        res = inputs[0] - inputs[1]
        self.output_shapes = K.int_shape(res)
        return res
    
    def compute_output_shape(self, input_shape):
        return self.output_shapes
''') 
开发者ID:microsoft,项目名称:MMdnn,代码行数:15,代码来源:keras2_emitter.py

示例14: create_res_texture_net

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def create_res_texture_net(input_rows, input_cols, num_res_filters=128,
        res_out_activation='linear', activation='relu', num_res_blocks=5, depth=3):
    '''Adds a series of residual blocks at each resolution scale, rather than just
    the minimium one.
    '''
    net = Graph()
    net.add_input('x', input_shape=(3, input_rows, input_cols))
    add_conv_block(net, 'in0', 'x', num_res_filters // 4, 9, activation=activation)
    last_name = 'in0'
    # scale down input to max depth with a series of strided convolutions
    for scale_i in range(depth):
        num_scale_filters = num_res_filters - scale_i * 8 # // (2 ** scale_i) # (depth - scale_i - 1))
        scale_name = 'down_{}'.format(scale_i)
        add_conv_block(net, scale_name, last_name, num_scale_filters, 3, subsample=(2, 2), activation=activation)
        last_name = scale_name
    # add a series of residual blocks at each scale, from smallest to largest
    for scale_i in reversed(range(depth)):
        num_scale_filters = num_res_filters - scale_i * 8 # // (2 ** scale_i) # (depth - scale_i - 1))
        last_scale_name = last_name
        for res_i in range(num_res_blocks):
            block_name = 'res_{}_{}'.format(scale_i, res_i)
            add_conv_block(net, block_name + '_b0', last_name, num_res_filters, 3, activation=activation)
            add_conv_block(net, block_name + '_b1', block_name + '_b0', num_res_filters, 1, activation='linear')
            if last_name == last_scale_name:
                # tranform residual connection to same number of filters
                add_conv_block(net, block_name + '_res', last_name, num_res_filters, 1, activation='linear')
            else:
                # no transform needed when the last node was part of the current residual block
                net.add_node(Layer(), block_name + '_res', last_name)
            net.add_node(Activation(res_out_activation), block_name, merge_mode='sum', inputs=[block_name + '_b1', block_name + '_res'])
            last_name = block_name
        # theano doesn't seem to support fractionally-strided convolutions at the moment
        up_name = 'up_{}'.format(scale_i)
        net.add_node(UpSampling2D(), up_name, last_name)
        last_name = up_name
        last_scale_name = up_name
    # final output
    add_conv_block(net, 'out', last_name, 3, 9, activation='linear')
    net.add_node(Activation('linear'), 'texture_rgb', 'out', create_output=True)
    return net 
开发者ID:awentzonline,项目名称:keras-rtst,代码行数:42,代码来源:girthy.py

示例15: get_h_given_x_layer

# 需要导入模块: from keras.layers import core [as 别名]
# 或者: from keras.layers.core import Layer [as 别名]
def get_h_given_x_layer(self, as_initial_layer=False):
        """
        Generates a new Dense Layer that computes mean of Bernoulli distribution p(h|x), ie. p(h=1|x).
        """
        if  as_initial_layer:
            layer = Dense(input_dim=self.input_dim, output_dim=self.hidden_dim, activation='sigmoid', weights=[self.W.get_value(), self.bh.get_value()])
        else:
            layer = Dense(output_dim=self.hidden_dim, activation='sigmoid', weights=[self.W.get_value(), self.bh.get_value()])
        return layer 
开发者ID:wuaalb,项目名称:keras_extensions,代码行数:11,代码来源:rbm.py


注:本文中的keras.layers.core.Layer方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。