fix Toeplitz convolution2d test

bnpm/tests/test_all.py

@@ -70,10 +70,9 @@ def test_toeplitz_convolution2d():
 
             try:
                 t = Toeplitz_convolution2d(x_shape=(stt[0][ii], stt[1][ii]), k=k, mode=mode, dtype=None)
-                out_t2d = t(x, batching=True, mode=mode)
-                out_t2d_s = t(scipy.sparse.csr_matrix(x), batching=True, mode=mode).toarray()
-                print(type(out_t2d), type(out_t2d_s))
                 out_sp = np.stack([scipy.signal.convolve2d(x_i.reshape(stt[0][ii], stt[1][ii]), k, mode=mode) for x_i in x], axis=0)
+                out_t2d = t(x, batching=True, mode=mode).reshape(3, out_sp.shape[1], out_sp.shape[2])
+                out_t2d_s = t(scipy.sparse.csr_matrix(x), batching=True, mode=mode).toarray().reshape(3, out_sp.shape[1], out_sp.shape[2])
             except Exception as e:
                 if mode == 'valid' and (stt[0][ii] < stt[2][ii] or stt[1][ii] < stt[3][ii]):
                     if 'x must be larger than k' in str(e):
@@ -93,6 +92,12 @@ def test_toeplitz_convolution2d():
 
             else:
                 print(f'C) test failed with batching==False, shapes:  x: {x.shape}, k: {k.shape} and mode: {mode}')
+                print(f"Failure analysis: \n")
+                print(f"Shapes: x: {x.shape}, k: {k.shape}, out_t2d: {out_t2d.shape}, out_t2d_s: {out_t2d_s.shape}, out_sp: {out_sp.shape}")
+                print(f"out_t2d: {out_t2d}")
+                print(f"out_t2d_s: {out_t2d_s}")
+                print(f"out_sp: {out_sp}")
+
                 success = False
                 break           
     print(f'success with all shapes and modes') if success else None