- name: assign_value inputs: [] attrs: - {typename: 'int[]', name: shape} - {typename: DataType, name: dtype} - {typename: 'Scalar[]', name: values, data_type: 'std::vector'} - {typename: Place, name: place, default_value: '{}'} outputs: - {typename: Tensor, name: out, optional: false, intermediate: false} no_need_buffer: null data_transform: null infer_meta: func: AssignValueInferMeta param: [shape, dtype] kernel: func: [assign_value] param: [shape, dtype, values] backend: ordered: true candidates: [place] layout: null data_type: ordered: false candidates: [dtype] to_complex_flag: [false] dispatch: {assign_value: null} force_backend: null inplace: null view: null backward: null - name: feed inputs: [] attrs: - {typename: str, name: name} - {typename: int, name: col} outputs: - {typename: Tensor, name: out, optional: false, intermediate: false} no_need_buffer: null data_transform: null inplace: null backward: null - name: fetch inputs: - typename: Tensor name: x optional: false no_need_buffer: false data_transform: {} attrs: - {typename: str, name: name} - {typename: int, name: col} outputs: - {typename: Tensor, name: out, optional: false, intermediate: false} no_need_buffer: null data_transform: null infer_meta: func: UnchangedInferMeta param: [x] kernel: func: [fetch] param: [x] backend: null layout: null data_type: null dispatch: {fetch: null} force_backend: null inplace: null backward: null - name: save_combine inputs: - typename: Tensor[] name: X optional: false no_need_buffer: false data_transform: {} attrs: - {typename: str, name: file_path} - {typename: bool, name: overwrite} - {typename: bool, name: save_as_fp16} - {typename: bool, name: save_to_memory} outputs: - {typename: Tensor, name: out, optional: true, intermediate: false} no_need_buffer: null data_transform: null kernel: func: [save_combine_tensor] param: [X, file_path, overwrite, save_as_fp16, save_to_memory] backend: null layout: null data_type: null dispatch: {fetch: null} force_backend: null inplace: null backward: null - name: load_combine inputs: [] attrs: - {typename: str, name: file_path} - {typename: bool, name: load_as_fp16} - {typename: bool, name: model_from_memory} outputs: - {typename: 'Tensor[]', name: Out, optional: true, intermediate: false} no_need_buffer: null data_transform: null kernel: func: [load_combine] param: [file_path, load_as_fp16, model_from_memory] backend: null layout: null data_type: null dispatch: {fetch: null} force_backend: null inplace: null backward: null - name: share_buffer_ inputs: - typename: Tensor[] name: x optional: false no_need_buffer: false data_transform: {} attrs: - {typename: 'bool[]', name: share_dims_and_dtype, default_value: '{}'} outputs: - {typename: 'Tensor[]', name: out, size: x.size(), optional: false, intermediate: false} - {typename: 'Tensor[]', name: xout, size: x.size(), optional: false, intermediate: false} no_need_buffer: null data_transform: null inplace: null backward: null - name: assert inputs: - typename: Tensor name: cond optional: false no_need_buffer: false data_transform: {} - typename: Tensor[] name: data optional: false no_need_buffer: false data_transform: {} attrs: - {typename: 'int64_t', name: summarize, default_value: '-1'} outputs: [] no_need_buffer: null data_transform: null inplace: null backward: null - name: print inputs: - typename: Tensor name: in optional: false no_need_buffer: false data_transform: {} attrs: - {typename: 'int', name: first_n} - {typename: 'str', name: message} - {typename: 'int', name: summarize} - {typename: 'bool', name: print_tensor_name, default_value: 'true'} - {typename: 'bool', name: print_tensor_type, default_value: 'true'} - {typename: 'bool', name: print_tensor_shape, default_value: 'true'} - {typename: 'bool', name: print_tensor_layout, default_value: 'true'} - {typename: 'bool', name: print_tensor_lod, default_value: 'true'} - {typename: 'str', name: print_phase, default_value: '"BOTH"'} - {typename: 'bool', name: is_forward, default_value: 'true'} outputs: - typename: Tensor name: out optional: false no_need_buffer: false data_transform: {} infer_meta: func: UnchangedInferMeta param: [in] kernel: func: [print_kernel] param: [in, first_n, message, summarize, print_tensor_name, print_tensor_type, print_tensor_shape, print_tensor_layout, print_tensor_lod, print_phase, is_forward ] backend: null layout: null data_type: null dispatch: {print: null} force_backend: null no_need_buffer: null data_transform: null inplace: null backward: null - name: add_n_ inputs: - typename: Tensor[] name: inputs optional: false no_need_buffer: false data_transform: {} attrs: [] outputs: - {typename: Tensor, name: out, optional: false, intermediate: false} no_need_buffer: null data_transform: null infer_meta: func: AddNInferMeta param: [inputs] kernel: func: [add_n] param: [inputs] backend: null layout: null data_type: null dispatch: {fetch: null} force_backend: null backward: add_n_grad - name: add_n_with_kernel inputs: - typename: Tensor[] name: inputs optional: false no_need_buffer: false data_transform: {} attrs: [] outputs: - {typename: Tensor, name: out, optional: false, intermediate: false} no_need_buffer: null data_transform: null infer_meta: func: AddNInferMeta param: [inputs] kernel: func: [add_n] param: [inputs] backend: null layout: null data_type: null dispatch: {fetch: null} force_backend: null backward: add_n_grad - name: write_to_array inputs: - typename: Tensor name: i optional: false no_need_buffer: false data_transform: {} - typename: Tensor name: x optional: false no_need_buffer: false data_transform: {} attrs: [] outputs: - {typename: 'Tensor[]', name: out, optional: false, intermediate: false} no_need_buffer: null data_transform: null backward: write_to_array_grad - name: lod_array_length inputs: - typename: Tensor[] name: x optional: false no_need_buffer: false data_transform: {} attrs: [] outputs: - {typename: 'Tensor', name: out, optional: false, intermediate: false} no_need_buffer: null data_transform: null - name: embedding_grad_sparse inputs: - typename: Tensor name: x optional: false no_need_buffer: false data_transform: {} - typename: Tensor name: weight optional: false no_need_buffer: false data_transform: {} - typename: Tensor name: out_grad optional: false no_need_buffer: false data_transform: {} attrs: - {typename: int64_t, name: padding_idx, default_value: '-1'} - {typename: bool, name: sparse, default_value: 'false'} outputs: - {typename: SelectedRows, name: weight_grad, optional: false, intermediate: false} no_need_buffer: null data_transform: null infer_meta: func: EmbeddingGradSparseInferMeta param: [weight] kernel: func: [embedding_sparse_grad] param: [x, weight, out_grad, padding_idx, sparse] backend: null layout: null data_type: ordered: false candidates: [weight] to_complex_flag: [false] dispatch: {embedding_sparse_grad: null} force_backend: null inplace: null view: null backward: null - name: shadow_feed inputs: - typename: Tensor name: x optional: false no_need_buffer: false data_transform: {} attrs: [] outputs: - {typename: Tensor, name: out, optional: false, intermediate: false} no_need_buffer: null data_transform: null infer_meta: func: UnchangedInferMeta param: [x] kernel: func: [shadow_feed] param: [x] backend: null layout: null data_type: null dispatch: {fetch: null} force_backend: null inplace: null backward: null