Higher rank tensors are indexed by passing multiple indices. Print("Reversed:", rank_1_tensor.numpy()) Print("Every other item:", rank_1_tensor.numpy()) Print("From 2, before 7:", rank_1_tensor.numpy()) Print("From 4 to the end:", rank_1_tensor.numpy()) Print("Before 4:", rank_1_tensor.numpy()) Indexing with a : slice keeps the axis: print("Everything:", rank_1_tensor.numpy()) Indexing with a scalar removes the axis: print("First:", rank_1_tensor.numpy()) colons, :, are used for slices: start:stop:step.negative indices count backwards from the end.TensorFlow follows standard Python indexing rules, similar to indexing a list or a string in Python, and the basic rules for NumPy indexing. This way feature vectors are contiguous regions of memory. Often axes are ordered from global to local: The batch axis first, followed by spatial dimensions, and features for each location last. While axes are often referred to by their indices, you should always keep track of the meaning of each. Print("Total number of elements (3*2*4*5): ", tf.size(rank_4_tensor).numpy())Įlements along the last axis of tensor: 5 Print("Elements along the last axis of tensor:", rank_4_tensor.shape)
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Print("Elements along axis 0 of tensor:", rank_4_tensor.shape) Print("Shape of tensor:", rank_4_tensor.shape) Print("Number of axes:", rank_4_tensor.ndim) Print("Type of every element:", rank_4_tensor.dtype) Tensors and tf.TensorShape objects have convenient properties for accessing these: rank_4_tensor = tf.zeros() Note: Although you may see reference to a "tensor of two dimensions", a rank-2 tensor does not usually describe a 2D space. Size: The total number of items in the tensor, the product shape vector.
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A scalar contains a single value, and no "axes".
#Element 3d 2.2 crash update
If you're familiar with NumPy, tensors are (kind of) like np.arrays.Īll tensors are immutable like Python numbers and strings: you can never update the contents of a tensor, only create a new one. You can see all supported dtypes at tf.dtypes.DType. Tensors are multi-dimensional arrays with a uniform type (called a dtype).