diff options
Diffstat (limited to 'verif/generator/tosa_test_gen.py')
| -rw-r--r-- | verif/generator/tosa_test_gen.py | 107 |
1 files changed, 52 insertions, 55 deletions
diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py index 28b3d28..71d7fcc 100644 --- a/verif/generator/tosa_test_gen.py +++ b/verif/generator/tosa_test_gen.py @@ -3172,64 +3172,54 @@ class TosaTestGen: return False def createDynamicOpLists(self): - - if "conv2d_TEMPLATE" not in self.TOSA_OP_LIST: - # Already created these lists (can occur when class is initialized more than once) - return - - # Dynamically create op lists for convolutions with a list of kernel sizes - if not self.args.level8k: - KERNELS_2D = [[1, 1], [2, 2], [3, 3], [5, 5], [3, 1], [1, 3]] - KERNELS_3D = [[1, 1, 1], [2, 1, 1], [1, 2, 1], [1, 1, 2]] - else: - bigK = self.TOSA_8K_LEVEL_MAX_KERNEL - KERNELS_2D = [[1, bigK], [bigK, 2]] - KERNELS_3D = [[1, bigK, 1], [2, 2, bigK]] - - for k in KERNELS_2D: - testName = "conv2d_{}x{}".format(k[0], k[1]) - self.TOSA_OP_LIST[testName] = self.TOSA_OP_LIST["conv2d_TEMPLATE"].copy() - self.TOSA_OP_LIST[testName]["filter"] = k - self.TOSA_OP_LIST[testName]["template"] = False - self.TOSA_OP_LIST[testName]["real_name"] = "conv2d" - - testName = "depthwise_conv2d_{}x{}".format(k[0], k[1]) - self.TOSA_OP_LIST[testName] = self.TOSA_OP_LIST[ - "depthwise_conv2d_TEMPLATE" - ].copy() - self.TOSA_OP_LIST[testName]["filter"] = k - self.TOSA_OP_LIST[testName]["template"] = False - self.TOSA_OP_LIST[testName]["real_name"] = "depthwise_conv2d" - - testName = "transpose_conv2d_{}x{}".format(k[0], k[1]) - self.TOSA_OP_LIST[testName] = self.TOSA_OP_LIST[ - "transpose_conv2d_TEMPLATE" - ].copy() - self.TOSA_OP_LIST[testName]["filter"] = k - self.TOSA_OP_LIST[testName]["template"] = False - self.TOSA_OP_LIST[testName]["real_name"] = "transpose_conv2d" - - for k in KERNELS_3D: - testName = "conv3d_{}x{}x{}".format(k[0], k[1], k[2]) - self.TOSA_OP_LIST[testName] = self.TOSA_OP_LIST["conv3d_TEMPLATE"].copy() - self.TOSA_OP_LIST[testName]["filter"] = k - self.TOSA_OP_LIST[testName]["template"] = False - self.TOSA_OP_LIST[testName]["real_name"] = "conv3d" - - # Delete any templates after having created any dynamic ops - # This is a two-pass operation because it's bad practice to delete - # keys from dictionaries while iterating - keyList = [] - for k in self.TOSA_OP_LIST: + # Find all the ops marked as templates + templateKeys = [] + for opName in self.TOSA_OP_LIST: try: - if self.TOSA_OP_LIST[k]["template"]: - keyList.append(k) - continue + if self.TOSA_OP_LIST[opName]["template"]: + templateKeys.append(opName) except KeyError: pass - for k in keyList: - del self.TOSA_OP_LIST[k] + bigK = self.TOSA_8K_LEVEL_MAX_KERNEL + + # Add dynamic ops based on kernel sizes + for opName in templateKeys: + assert opName.endswith("_TEMPLATE"), "Found incorrect template" + realName = opName[: len(opName) - len("_TEMPLATE")] + template = self.TOSA_OP_LIST[opName] + k_rank = 3 if realName == "conv3d" else 2 + + # Choose kernels to build tests for from the template or args + if self.args.level8k: + if k_rank == 3: + kernels = [[1, bigK, 1], [2, 2, bigK]] + else: + kernels = [[1, bigK], [bigK, 2]] + else: + kernels = [] + if len(self.args.conv_kernels) > 0: + kernels = [k for k in self.args.conv_kernels if len(k) == k_rank] + if len(kernels) == 0: + logger.debug( + f"{realName} op using defaults as no rank {k_rank} kernels found in {self.args.conv_kernels}" + ) + if len(kernels) == 0: + # Fallback to use the defined template kernels + kernels = self.TOSA_OP_LIST[opName]["filter"] + + # Dynamically create ops for listed kernel sizes + for k in kernels: + kernelStr = "x".join([str(d) for d in k]) + testName = f"{realName}_{kernelStr}" + kernelOp = template.copy() + kernelOp["filter"] = k + kernelOp["template"] = False + kernelOp["real_name"] = realName + self.TOSA_OP_LIST[testName] = kernelOp + + # Delete the template after having created the dynamic ops + del self.TOSA_OP_LIST[opName] def initOpListDefaults(self): """Fill in default fields for ops if they aren't already specified. @@ -3333,6 +3323,9 @@ class TosaTestGen: DEFAULT_RANK_RANGE = (1, gtu.MAX_TENSOR_RANK) + KERNELS_2D = [[1, 1], [2, 2], [3, 3], [5, 5], [3, 1], [1, 3]] + KERNELS_3D = [[1, 1, 1], [2, 1, 1], [1, 2, 1], [1, 1, 2]] + TOSA_OP_LIST = { # Tensor operators "argmax": { @@ -3426,6 +3419,8 @@ class TosaTestGen: "data_gen": { "fp": (gtu.DataGenType.DOT_PRODUCT,), }, + "broadcastable_bias": True, + "filter": KERNELS_2D, "template": True, }, # Templated operator. Filled in by createDynamicOpLists @@ -3460,13 +3455,13 @@ class TosaTestGen: "data_gen": { "fp": (gtu.DataGenType.DOT_PRODUCT,), }, + "filter": KERNELS_3D, "template": True, }, # Templated operator. Filled in by createDynamicOpLists "depthwise_conv2d_TEMPLATE": { "op": Op.DEPTHWISE_CONV2D, "operands": (1, 2), - "filter": [1, 1], "rank": (4, 4), "build_fcn": ( build_depthwise_conv2d, @@ -3495,6 +3490,7 @@ class TosaTestGen: "data_gen": { "fp": (gtu.DataGenType.DOT_PRODUCT,), }, + "filter": KERNELS_2D, "template": True, }, "fully_connected": { @@ -3608,6 +3604,7 @@ class TosaTestGen: "data_gen": { "fp": (gtu.DataGenType.DOT_PRODUCT,), }, + "filter": KERNELS_2D, "template": True, }, # Activation functions |