diff --git a/op_list.md b/op_list.md index aff73baf9a9f9447e215972c44479709b8a4c2d0..8b47b62b0300d9532a4fba974f923b758a2154e2 100644 --- a/op_list.md +++ b/op_list.md @@ -1,5 +1,5 @@ # X2Paddle支持OP列表 -> 目前X2Paddle支持50+的TensorFlow OP，30+的Caffe Layer，覆盖了大部分CV分类模型常用的操作。我们在如下列表中给出了目前X2Paddle支持的全部OP。 +> 目前X2Paddle支持70+的TensorFlow OP，30+的Caffe Layer，覆盖了大部分CV分类模型常用的操作。我们在如下列表中给出了目前X2Paddle支持的全部OP。 **注：** 目前，部分OP暂未支持，如您在转换过程中出现OP不支持的情况，可自行添加或反馈给我们。欢迎通过[ISSUE反馈](https://github.com/PaddlePaddle/X2Paddle/issues/new)的方式告知我们(模型名，代码实现或模型获取方式)，我们会及时跟进：） @@ -7,20 +7,24 @@ | 序号 | OP | 序号 | OP | 序号 | OP | 序号 | OP | |------|------|------|------|------|------|------|------| -| 1 | Relu | 2 | Relu6 | 3 | Shape | 4 | Abs | -| 5 | Sigmoid | 6 | Exp | 7 | Rsqrt | 8 | swish_f32 | -| 9 | Tanh | 10 | LeakyRelu | 11 | Add | 12 | RealDiv | -| 13 | Sub | 14 | Maximum | 15 | Mul | 16 | FloorDiv | -| 17 | Placeholder | 18 | Const | 19 | Transpose | 20 | FusedBatchNorm | -| 21 | Conv2D | 22 | BiasAdd | 23 | MaxPool | 24 | DepthwiseConv2dNative | -| 25 | Reshape | 26 | AvgPool | 27 | SplitV | 28 | SquaredDifference | -| 29 | Tile | 30 | Pack | 31 | Pad | 32 | ResizeBilinear | -| 33 | Mean | 34 | MatMul | 35 | ArgMax | 36 | StridedSlice | -| 37 | Slice | 38 | Sum | 39 | Max | 40 | Conv2DBackpropInput | -| 41 | Cast | 42 | Split | 43 | Squeeze | 44 | ResizeNearestNeighbor | -| 45 | Softmax | 46 | Range | 47 | ConcatV2 | 48 | MirrorPad | -| 49 | Identity | 50 | GreaterEqual | 51 | StopGradient | 52 | Minimum | -| 53 | RadnomUniform | 54 | Fill | 55 | Floor | 56 | DepthToSpace | +| 1 | Relu | 2 | Relu6 | 3 | Shape | 4 | Abs | +| 5 | Sigmoid | 6 | Exp | 7 | Rsqrt | 8 | swish_f32 | +| 9 | Tanh | 10 | LeakyRelu | 11 | Add | 12 | RealDiv | +| 13 | Sub | 14 | Maximum | 15 | Mul | 16 | FloorDiv | +| 17 | Placeholder | 18 | Const | 19 | Transpose | 20 | FusedBatchNorm | +| 21 | Conv2D | 22 | BiasAdd | 23 | MaxPool | 24 | DepthwiseConv2dNative | +| 25 | Reshape | 26 | AvgPool | 27 | SplitV | 28 | SquaredDifference | +| 29 | Tile | 30 | Pack | 31 | Pad | 32 | ResizeBilinear | +| 33 | Mean | 34 | MatMul | 35 | ArgMax | 36 | StridedSlice | +| 37 | Slice | 38 | Sum | 39 | Max | 40 | Conv2DBackpropInput | +| 41 | Cast | 42 | Split | 43 | Squeeze | 44 | ResizeNearestNeighbor | +| 45 | Softmax | 46 | Range | 47 | ConcatV2 | 48 | MirrorPad | +| 49 | Identity | 50 | GreaterEqual | 51 | StopGradient | 52 | Minimum | +| 53 | RadnomUniform | 54 | Fill | 55 | Floor | 56 | DepthToSpace | +| 57 | Sqrt | 58 | Softplus | 59 | Erf | 60 | AddV2 | +| 61 | LessEqual | 62 | BatchMatMul | 63 | BatchMatMulV2 | 64 | ExpandDims | +| 65 | BatchToSpaceND | 66 | SpaceToBatchND | 67 | OneHot | 68 | Pow | +| 69 | All | 70 | GatherV2 | 71 | IteratorV2 | | | ## Caffe diff --git a/x2paddle/op_mapper/tf_op_mapper_nhwc.py b/x2paddle/op_mapper/tf_op_mapper_nhwc.py index 2bb0adeac0c7cfc11030be01d7366b21cc86d6bd..a5198cc780203722042b8ae043fb169b94eeb3be 100644 --- a/x2paddle/op_mapper/tf_op_mapper_nhwc.py +++ b/x2paddle/op_mapper/tf_op_mapper_nhwc.py @@ -299,6 +299,10 @@ class TFOpMapperNHWC(OpMapper): data_format = node.get_attr("data_format").decode() pad_mode = node.get_attr("padding").decode() channel_first = data_format == "NCHW" + if data_format == "NHWC": + n, h, w, c = input.out_shapes[0] + else: + n, c, h, w = input.out_shapes[0] if kernel.layer_type == 'Const': kernel_value = kernel.value @@ -329,10 +333,15 @@ class TFOpMapperNHWC(OpMapper): "dilation": dilations[2:4], "padding": string(pad_mode) } - if hasattr(node, 'dilation') and attr['dilation'] == [1, 1]: if len(node.dilation) == 1: attr['dilation'] = [1, node.dilation[0]] + + if c == -1: + reshape_attr = {"shape": [0, k_size[2], 0, 0]} + node.fluid_code.add_layer( + "reshape", inputs=input, output=input, param_attr=reshape_attr) + node.fluid_code.add_layer( "conv2d", inputs=input, output=node, param_attr=attr) if not channel_first: @@ -748,11 +757,12 @@ class TFOpMapperNHWC(OpMapper): self.add_omit_nodes(begin.layer_name, node.layer_name) begin = begin.value.tolist() else: - begin = begin - shape = begin.out_shapes[0] - attr = {"shape": shape} - node.fluid_code.add_layer( - "reshape", inputs=begin, output=begin, param_attr=attr) + begin = self.decoder.infer_tensor(begin).tolist() + +# shape = begin.out_shapes[0] +# attr = {"shape": shape} +# node.fluid_code.add_layer( +# "reshape", inputs=begin, output=begin, param_attr=attr) if size.layer_type == "Const": self.add_omit_nodes(size.layer_name, node.layer_name) size = size.value.tolist() diff --git a/x2paddle/optimizer/tf_optimizer.py b/x2paddle/optimizer/tf_optimizer.py index 6d3c0cdd017c6d046451e5837d2b75ef649cd6a8..daeda64dceb8cdfa31cf10fa31edb0aae176170e 100644 --- a/x2paddle/optimizer/tf_optimizer.py +++ b/x2paddle/optimizer/tf_optimizer.py @@ -863,6 +863,9 @@ class TFOptimizer(object): weight = numpy.expand_dims(weight, 2) weight = numpy.expand_dims(weight, 3) self.op_mapper.weights[in_nodes3[0].layer_name] = weight + # fix bug in Paddle1.8.3 and may change in next version. + self.op_mapper.weights[in_nodes3[0].layer_name + + '_1'] = weight.reshape(1, -1) in_nodes3[0].fluid_code.layers[0].param_attr["shape"] = [ 1, in_shape[-1], 1, 1 ] @@ -885,7 +888,7 @@ class TFOptimizer(object): node.fluid_code.clear() attr = { "mode": string(mode), - "param_attr": string(in_nodes3[0].layer_name) + "param_attr": string(in_nodes3[0].layer_name + "_1") } node.fluid_code.add_layer( diff --git a/x2paddle_model_zoo.md b/x2paddle_model_zoo.md index 0bfc0f3a35c11e7fa0585b5649d9661d8a59e943..464abdf547b1c9c7a3698c05579131426c44b59e 100644 --- a/x2paddle_model_zoo.md +++ b/x2paddle_model_zoo.md @@ -1,5 +1,5 @@ # X2Paddle模型测试库 -> 目前X2Paddle支持50+的TensorFlow OP，40+的Caffe Layer，覆盖了大部分CV分类模型常用的操作。我们在如下模型列表中测试了X2Paddle的转换。 +> 目前X2Paddle支持70+的TensorFlow OP，40+的Caffe Layer，覆盖了大部分CV分类模型常用的操作。我们在如下模型列表中测试了X2Paddle的转换。 **注：** 受限于不同框架的差异，部分模型可能会存在目前无法转换的情况，如TensorFlow中包含控制流的模型，NLP模型等。对于CV常见的模型，如若您发现无法转换或转换失败，存在较大diff等问题，欢迎通过[ISSUE反馈](https://github.com/PaddlePaddle/X2Paddle/issues/new)的方式告知我们(模型名，代码实现或模型获取方式)，我们会及时跟进：）