pd_op.yaml

- 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: 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: {}
  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: shaddow_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: [shaddow_feed]
    param: [x]
    backend: null
    layout: null
    data_type: null
    dispatch: {fetch: null}
    force_backend: null
  inplace: null
  backward: null