Fixes JSON Payload input shapes in Pandas DataFrame content type section of User Guide.
For example DataFrame:
A
B
C
a1
b1
c1
a2
b2
c2
a3
b3
c3
a4
b4
c4
All inputs in JSON payload had "shape": [3] (the number of columns in the DataFrame) instead of "shape": [4] (the number of rows in the DataFrame).
This PR assumes that #1625 is in fact a bug, and that the shape values should not have an extra dimension added to them. If that assumption is incorrect, I would recommend also adding a disclaimer to this section like the one seen in the Numpy Array section before it:
Note
By default, MLServer will always assume that an array with a single-dimensional shape, e.g. [N], is equivalent to [N, 1]. That is, each entry will be treated like a single one-dimensional data point (i.e. instead of a [1, D] array, where the full array is a single D-dimensional data point). To avoid any ambiguity, where possible, the Numpy codec will always explicitly encode [N] arrays as [N, 1].
Closes #1678
Fixes JSON Payload input shapes in Pandas DataFrame content type section of User Guide.
For example DataFrame:
All inputs in JSON payload had
"shape": [3]
(the number of columns in the DataFrame) instead of"shape": [4]
(the number of rows in the DataFrame).This PR assumes that #1625 is in fact a bug, and that the shape values should not have an extra dimension added to them. If that assumption is incorrect, I would recommend also adding a disclaimer to this section like the one seen in the Numpy Array section before it: