matmul code refactor

tests/common/test_op/matmul.py → python/akg/ops/nn/matmul.py

@@ -33,7 +33,7 @@ matmul_set_dim_map = {
 }
 
 
-def matmul_set_dim(A, B, b, out_dtype, left_format, right_format, output_format, adj_x, adj_y, has_bias, attrs):
+def matmul_set_dim(A, B, b, out_dtype, left_format, right_format, output_format, adj_x, adj_y, attrs):
     shape_A = A.shape
     shape_B = B.shape
     bias = 0 if b is None else 1
@@ -259,7 +259,7 @@ def matmul4D_compute(x, y, bias_value, out_dtype, left_format, right_format, out
 
 
 @ct_util.reg_set_dim_func(matmul_set_dim)
-def matmul(x, y, b, out_dtype, left_format="zZ", right_format="nZ", out_format="zN", transpose_x=False, transpose_y=False, has_bias=False, attrs=None):
+def matmul(x, y, b, out_dtype, left_format="zZ", right_format="nZ", out_format="zN", transpose_x=False, transpose_y=False, attrs=None):
     """
     Computes matrix multiplication x * y + b.
 
@@ -273,7 +273,6 @@ def matmul(x, y, b, out_dtype, left_format="zZ", right_format="nZ", out_format="
         out_format: str. Data format of output tensor. Supported data format list ["zZ", "nZ", "zN"].
         transpose_x: Boolean. Specifies whether x is transposed or not. 
         transpose_y: Boolean. Specifies whether y is transposed or not.
-        has_bias: Boolean. Specifies whether bias tensor exists or not.
         attrs: Dict. Used in matmul computation.
 
     Note:

tests/common/test_op/matmul4d_ad.py

@@ -15,7 +15,7 @@
 """operator dsl function: matmul4d_ad"""
 import akg.tvm
 import akg
-from test_op import matmul
+from akg.ops.nn import matmul
 from akg.utils import custom_tiling as ct_util
 
 

tests/common/test_run/matmul_run.py

@@ -19,7 +19,7 @@ from gen_random import random_gaussian
 import numpy as np
 import akg.backend as cce
 from akg.utils import kernel_exec as utils
-from test_op import matmul
+from akg.ops.nn import matmul
 from base import get_rtol_atol
 from tensorio import compare_tensor
 
@@ -353,9 +353,9 @@ def matmul_compile(shape_x, shape_y, bias, left_format, right_format, output_for
     has_bias = False
     if bias == 1:
         has_bias = True
-    op_attrs = [out_dtype, left_format, right_format, output_format, adj_x, adj_y, has_bias, attrs]
+    op_attrs = [out_dtype, left_format, right_format, output_format, adj_x, adj_y, attrs]
     if has_bias == False:
         input_shapes = [shape_xx, shape_yy]
         input_types = [dtype, dtype]
-        op_attrs = [None, out_dtype, left_format, right_format, output_format, adj_x, adj_y, has_bias, attrs]
+        op_attrs = [None, out_dtype, left_format, right_format, output_format, adj_x, adj_y, attrs]
     return utils.op_build_test(matmul.matmul, input_shapes, input_types, op_attrs, kernel_name, attrs)

tests/fuzz/tune/autotuning/kernel_compiler.py

@@ -21,7 +21,7 @@ from akg.utils import custom_tiling as ct_util
 from akg.ops.nn import conv_bn1
 from akg.ops.nn import conv, conv_backprop_input, conv_backprop_filter, batchmatmul
 from akg.backend import build_module
-from test_op import matmul
+from akg.ops.nn import matmul
 from test_run import batchmatmul_run, matmul_run
 from .type_definitions import ConvDesc, ConvBackpropDesc, MatmulCubeDesc, ConvConfig, ConvBackpropInputConfig, ConvBackpropFilterConfig, MatmulCubeConfig