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Try running a SPA associative memory with 1-dimensional vectors. We get output like:
Transpose A: 111 m: 1 n: 10 leading_dim_A: 1 X.stride1: 1 Y.stride1: 1 A_label: <Connection from <Node "element output"> to <Node "output">>.weights X_label: <Node "element output">.in[(slice(None, None, None),)] Y_label: <Connection from <Node "element output"> to <Node "output">>.weighted lda must be >= MAX(N,1): lda=1 N=10Parameter 7 to routine cblas_dgemv was incorrect
The first block of output is diagnostic info from added print statements. Has something to do with treating a matrix as a vector.
The text was updated successfully, but these errors were encountered:
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Try running a SPA associative memory with 1-dimensional vectors. We get output like:
The first block of output is diagnostic info from added print statements. Has something to do with treating a matrix as a vector.
The text was updated successfully, but these errors were encountered: