theano 编程细节（二）

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type/dtype

dtype：data type

>> x = T.matrix()>> x.typeTensorType(float64, matrix)>> x.dtype'float64'

numpy 下的多维数组到 theano.shared

Place the data into shared variables. This allows theano to copy the data to the GPU, if one is available.

def load_data_shared(filename='./data/mnist.pkl.gz'):    with gzip.open(filename) as fp:        training_data, valid_data, test_data = pickle.load(fp)    def shared_data(data):        shared_x = theano.shared(                np.asarray(data[0], dtype=theano.config.floatX), borrow=True)        shared_y = theano.shared(                np.asarray(data[1], dtype=theano.config.floatX), borrow=True)        return shared_x, share_y    return shared_data(training_data), shared_data(valid_data), shared_data(test_data)

theano.function 的参数

def function(inputs, outputs=None, mode=None, updates=None, givens=None,             no_default_updates=False, accept_inplace=False, name=None,             rebuild_strict=True, allow_input_downcast=None, profile=None,             on_unused_input=None):                         # 常用的一般为 inputs，outputs，updates，givens

theano.tensor.var.TensorVariable

>> import theano.tensor as T>> inpt = T.tensor4(name='inpt')>> type(inpt)theano.tensor.var.TensorVariable>> inpt.ndim4>> inpt.dtype'float64'

所谓 theano.config.floatX

>> type(theano.config.floatX)str>> theano.config.floatX'float64'

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