Hi All, I get getting the following message at the end of output after running my mnist dataset program in the Spyder IDE:
*Init signature:Dense( units, activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, **kwargs,)Docstring: Just your regular densely-connected NN layer.`Dense` implements the operation:`output = activation(dot(input, kernel) + bias)`where `activation` is the element-wise activation functionpassed as the `activation` argument, `kernel` is a weights matrixcreated by the layer, and `bias` is a bias vector created by the layer(only applicable if `use_bias` is `True`).Note: if the input to the layer has a rank greater than 2, thenit is flattened prior to the initial dot product with `kernel`.# Example```python # as first layer in a sequential model: model = Sequential() model.add(Dense(32, input_shape=(16,))) # now the model will take as input arrays of shape (*, 16) # and output arrays of shape (*, 32) # after the first layer, you don't need to specify # the size of the input anymore: model.add(Dense(32))```# Arguments units: Positive integer, dimensionality of the output space. activation: Activation function to use (see [activations](../activations.md)). If you don't specify anything, no activation is applied (ie. "linear" activation: `a(x) = x`). use_bias: Boolean, whether the layer uses a bias vector. kernel_initializer: Initializer for the `kernel` weights matrix (see [initializers](../initializers.md)). bias_initializer: Initializer for the bias vector (see [initializers](../initializers.md)). kernel_regularizer: Regularizer function applied to the `kernel` weights matrix (see [regularizer](../regularizers.md)). bias_regularizer: Regularizer function applied to the bias vector (see [regularizer](../regularizers.md)). activity_regularizer: Regularizer function applied to the output of the layer (its "activation"). (see [regularizer](../regularizers.md)). kernel_constraint: Constraint function applied to the `kernel` weights matrix (see [constraints](../constraints.md)). bias_constraint: Constraint function applied to the bias vector (see [constraints](../constraints.md)).# Input shape nD tensor with shape: `(batch_size, ..., input_dim)`. The most common situation would be a 2D input with shape `(batch_size, input_dim)`.# Output shape nD tensor with shape: `(batch_size, ..., units)`. For instance, for a 2D input with shape `(batch_size, input_dim)`, the output would have shape `(batch_size, units)`.File: c:\programdata\anaconda3\lib\site-packages\keras\layers\core.pyType: typeSubclasses: * I did not choose any help topic. even though the above help message is comming at the end of output. Is this an error in the code or something to do with settings. Thanks and Regards, Vivek -- You received this message because you are subscribed to the Google Groups "spyder" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/spyderlib/8840f0f7-7145-44ea-8566-56b27645f2cf%40googlegroups.com.
