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Hi Radjen! ndarrays are nothing but tensors. So there is no need to convert them into tensors - they are tensors by definition! Best, The 365 Team.

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tensorflow tensor to numpy failed to convert a numpy array to a tensor keras valueerror: can't convert non-rectangular python sequence How to convert a TensorFlow tensor to a NumPy array in Python, ndarray to a tensor - it has an invalid type. The only supported types are: double, float...

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Define inputs as numpy arrays ( input-ids, token-ids and attention-mask ) for BERT. Define an output variable which also is a numpy array which has shape of batch X num_of_classes. If your model is not BERT, then define a zeros array of shape same as your model output.

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Hi Radjen! ndarrays are nothing but tensors. So there is no need to convert them into tensors - they are tensors by definition! Best, The 365 Team.在Numpy中索引可以支持Bool型的索引，例如： 此处的Index是一个numpy array,其元素类型就是我们标题中提及的：numpy,bool_。 但是Pytorch中不支持讲numpy.bool_类型转化为Tensor。这就导致了标题所示的错误: Type error: can't convert np.ndarray of type numpy.bool_.

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🚀Feature. Let the dtype keyword argument of torch.as_tensor be either a np.dtype or torch.dtype.. Motivation. Suppose I have two numpy arrays with different types and I want to convert one of them to a torch tensor with the type of the other array.

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torchは基本的にnumpyとさして変わりません。numpy.arrayにあってtorch.Tensorにはないものなども実際はあるのですが、やりたいことは大抵できるでしょう。 torch.autograd.Variable. さて、お待ちかねのPytorchに入っていきます。 To convert back from tensor to numpy array you can simply run .eval() on the transformed tensor. import tensorflow as tf W1 = tf.Variable(tf.random_uniform([1], -1.0, 1.0)) init = tf.global_variables_initializer() sess = tf.Session() sess.run(init) array = W1.eval(sess) print (array).

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