- python - What does `view ()` do in PyTorch? - Stack Overflow
18 torch Tensor view() Simply put, torch Tensor view() which is inspired by numpy ndarray reshape() or numpy reshape(), creates a new view of the tensor, as long as the new shape is compatible with the shape of the original tensor Let's understand this in detail using a concrete example
- What does `-1` of `view()` mean in PyTorch? - Stack Overflow
In this view x view(-1) is a weird flatten layer but missing the squeeze (i e adding a dimension of 1) Adding this squeeze or removing it is usually important for the code to actually run
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- Can we pass parameters to a view in SQL? - Stack Overflow
A view is a stored sql text of a select query Parameters are out of the discussion When your stored query returns the column where you want to filter with, you can do it in the calling query E g "SELECT * FROM v_emp WHERE emp_id = ?"
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View, group share contacts You can organize the people and businesses in Contacts using labels You can use the Contacts app to find someone’s contact info or organize contacts with labels like "friends" or "family "
- Whats the difference between `reshape()` and `view()` in PyTorch?
torch view has existed for a long time It will return a tensor with the new shape The returned tensor will share the underling data with the original tensor See the documentation here On the other hand, it seems that torch reshape has been introduced recently in version 0 4 According to the document, this method will Returns a tensor with the same data and number of elements as input, but
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