The shape attribute for numpy arrays returns the dimensions of the array. If Y has n rows and m columns, then Y.shape is (n,m). So Y.shape[0] is n.

Shape n, expresses the shape of a 1D array with n items, and n, 1 the shape of a n-row x 1-column array. (R,) and (R,1) just add (useless) parentheses but still express respectively 1D and 2D array …

Nov 30, 2017 · yourarray.shape or np.shape() or np.ma.shape() returns the shape of your ndarray as a tuple; And you can get the (number of) dimensions of your array using yourarray.ndim or np.ndim(). …

You can think of a placeholder in TensorFlow as an operation specifying the shape and type of data that will be fed into the graph.placeholder X defines that an unspecified number of rows of shape (128, …

Jun 4, 2015 · I already know how to set the opacity of the background image but I need to set the opacity of my shape object. In my Android app, I have it like this: and I want to make this black area …

Oct 22, 2018 · Shape (in the numpy context) seems to me the better option for an argument name. The actual relation between the two is size = np.prod(shape) so the distinction should indeed be a bit …

Mar 1, 2014 · I'm new to python and numpy in general. I read several tutorials and still so confused between the differences in dim, ranks, shape, aixes and dimensions. My mind seems to be stuck at …

Jan 9, 2014 · 8 list object in python does not have 'shape' attribute because 'shape' implies that all the columns (or rows) have equal length along certain dimension. Let's say list variable a has following …

May 24, 2016 · Still, performance-wise, the difference should be negligible except for a giant giant 2D dataframe. So in line with the previous answers, df.shape is good if you need both dimensions, for a …

For example, output shape of Dense layer is based on units defined in the layer where as output shape of Conv layer depends on filters. Another thing to remember is, by default, last dimension of any …