From 33f29a22d3d99b6c37fd729d92e802384ef486d2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E8=90=9D=E5=8D=9C=E8=8F=9C?= Date: Mon, 14 Feb 2022 16:26:10 +0800 Subject: [PATCH] fix pytengine example error (#1279) * apply code-format changes * fix python example error --- examples/classification.py | 1 + examples/landmark.py | 1 + examples/mobilenet_ssd.py | 1 + examples/retinaface.py | 2 +- tools/convert_tool/onnx/onnx2tengine.cpp | 4 +--- tools/save_graph/tm2_op_save.cpp | 3 +-- 6 files changed, 6 insertions(+), 6 deletions(-) diff --git a/examples/classification.py b/examples/classification.py index e1ca9f14..49f29a63 100644 --- a/examples/classification.py +++ b/examples/classification.py @@ -50,6 +50,7 @@ def main(args): data = ((data - img_mean) * scale).astype(np.float32) data = np.ascontiguousarray(data.transpose((2, 0, 1))) assert data.dtype == np.float32 + data = data.copy() graph = tg.Graph(None, 'tengine', tm_file) input_tensor = graph.getInputTensor(0, 0) diff --git a/examples/landmark.py b/examples/landmark.py index fc82c84a..e005c0bd 100755 --- a/examples/landmark.py +++ b/examples/landmark.py @@ -60,6 +60,7 @@ def main(args): data = ((data - img_mean) * scale[0]).astype(np.float32) data = data.transpose((2, 0, 1)) assert data.dtype == np.float32 + data = data.copy() graph = tg.Graph(None, 'tengine', tm_file) input_tensor = graph.getInputTensor(0, 0) diff --git a/examples/mobilenet_ssd.py b/examples/mobilenet_ssd.py index 9cdc7c8b..4ac30487 100755 --- a/examples/mobilenet_ssd.py +++ b/examples/mobilenet_ssd.py @@ -63,6 +63,7 @@ def main(args): data = ((data - img_mean) * DEFAULT_SCALE).astype(np.float32) data = data.transpose((2, 0, 1)) assert data.dtype == np.float32 + data = data.copy() graph = tg.Graph(None, 'tengine', tm_file) input_tensor = graph.getInputTensor(0, 0) diff --git a/examples/retinaface.py b/examples/retinaface.py index cf01db30..68710b56 100755 --- a/examples/retinaface.py +++ b/examples/retinaface.py @@ -322,7 +322,7 @@ def main(args): #image_data = image_data.transpose((2, 0, 1)).astype(np.float32) image_data = np.ascontiguousarray(image_data.transpose((2, 0, 1)).astype(np.float32)) - + image_data = image_data.copy() #print("img_h, img_w, img_c: %d, %d, %d" %(img_h, img_w, img_c)) input_tensor = graph.getTensorByName(input_name) diff --git a/tools/convert_tool/onnx/onnx2tengine.cpp b/tools/convert_tool/onnx/onnx2tengine.cpp index db45da4d..34a1fb7f 100644 --- a/tools/convert_tool/onnx/onnx2tengine.cpp +++ b/tools/convert_tool/onnx/onnx2tengine.cpp @@ -2132,9 +2132,7 @@ static int load_resize(ir_graph_t* graph, ir_node_t* node, const onnx::NodeProto interp_param->width_scale = 0; std::string coordinate_transformation_mode = GetAttributeOrDefault(onnx_node, "coordinate_transformation_mode", "half_pixel"); - TASSERT(coordinate_transformation_mode == "half_pixel" || - coordinate_transformation_mode == "align_corners" || - coordinate_transformation_mode == "asymmetric"); + TASSERT(coordinate_transformation_mode == "half_pixel" || coordinate_transformation_mode == "align_corners" || coordinate_transformation_mode == "asymmetric"); int align_corner = (coordinate_transformation_mode == "align_corners"); if (onnx_node.input_size() == 1) diff --git a/tools/save_graph/tm2_op_save.cpp b/tools/save_graph/tm2_op_save.cpp index 6e0a1ce1..1ed7c038 100644 --- a/tools/save_graph/tm2_op_save.cpp +++ b/tools/save_graph/tm2_op_save.cpp @@ -749,7 +749,6 @@ tm_uoffset_t SaveTmMinimumOp(void* const start_ptr, tm_uoffset_t* cur_pos, ir_no return WriteTmObject(start_ptr, cur_pos, &tm_op, sizeof(TM2_Operator)); } - tm_uoffset_t SaveTmSqueezeOp(void* const start_ptr, tm_uoffset_t* cur_pos, ir_node_t* node) { struct squeeze_param* p = (struct squeeze_param*)node->op.param_mem; @@ -1608,7 +1607,7 @@ op_save_t SaveTmOpFunc(uint32_t op_type) case OP_MINIMUM: return SaveTmMinimumOp; default: - fprintf(stderr, "Operator #%d not supported in tengine model yet\n",op_type); + fprintf(stderr, "Operator #%d not supported in tengine model yet\n", op_type); return nullptr; } } -- GitLab