【PIR OpTest Fix No.13】 Fix test_partial_concat_op

paddle/fluid/pir/dialect/op_generator/ops_api_gen.py

@@ -181,6 +181,7 @@
     'prune_gate_by_capacity',
     'push_sparse_v2',
     'push_sparse_v2_',
+    'partial_concat',
     'partial_send',
     'partial_recv',
     'partial_allgather',

paddle/fluid/pir/dialect/operator/ir/ops.yaml

@@ -1189,6 +1189,16 @@
     func : partial_allgather
   inplace : (x -> out)
 
+- op : partial_concat
+  args : (Tensor[] x, int start_index = 0, int length = -1)
+  output : Tensor(out)
+  infer_meta :
+    func : PartialConcatInferMeta
+  kernel :
+    func : partial_concat
+    data_type : x
+  backward : partial_concat_grad
+
 - op : partial_recv
   args : (int ring_id = 0, int peer = 0, DataType dtype=DataType::FLOAT32, int[] out_shape= {}, bool use_calc_stream = false, int num = 1, int id = 0)
   output : Tensor(out)

paddle/fluid/pir/dialect/operator/ir/ops_backward.yaml

@@ -580,6 +580,16 @@
   composite : pad_grad(x, out_grad, paddings, pad_value, x_grad)
   backward : pad_double_grad
 
+- backward_op : partial_concat_grad
+  forward : partial_concat (Tensor[] x, int start_index = 0, int length = -1) -> Tensor(out)
+  args : (Tensor[] x, Tensor out_grad, int start_index, int length)
+  output : Tensor[](x_grad){x.size()}
+  infer_meta :
+    func : PartialConcatGradInferMeta
+    param : [x]
+  kernel :
+    func : partial_concat_grad
+
 - backward_op : pool2d_double_grad
   forward : pool2d_grad(Tensor x, Tensor out, Tensor grad_out, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm) -> Tensor(grad_x)
   args : (Tensor x, Tensor grad_x_grad, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm)

paddle/fluid/pir/dialect/operator/utils/utils.cc

@@ -73,6 +73,8 @@ const std::unordered_set<std::string> LegacyOpList = {
     SoftReluGradOp::name(),
     MatchMatrixTensorOp::name(),
     MatchMatrixTensorGradOp::name(),
+    PartialConcatOp::name(),
+    PartialConcatGradOp::name(),
     NceOp::name(),
     NceGradOp::name(),
     LrnOp::name(),

paddle/phi/api/yaml/op_compat.yaml

@@ -2475,6 +2475,15 @@
   outputs :
     out : Out
 
+- op : partial_concat
+  backward : partial_concat_grad
+  inputs :
+    x : X
+  outputs :
+    out : Out
+  extra :
+    attrs : [bool use_mkldnn = false]
+
 - op : partial_recv
   outputs :
     out : Out

paddle/phi/infermeta/backward.cc

@@ -850,6 +850,16 @@ void NanmedianGradInferMeta(const MetaTensor& x,
   x_grad->set_dtype(x.dtype());
 }
 
+void PartialConcatGradInferMeta(const std::vector<const MetaTensor*>& xs,
+                                std::vector<MetaTensor*> x_grads) {
+  auto input_num = xs.size();
+  for (size_t i = 0; i < input_num; i++) {
+    auto x_dims = xs[i]->dims();
+    x_grads[i]->set_dims(x_dims);
+    x_grads[i]->set_dtype(xs[i]->dtype());
+  }
+}
+
 void NceGradInferMeta(const MetaTensor& input,
                       const MetaTensor& bias,
                       const MetaTensor& weight,

paddle/phi/infermeta/backward.h

@@ -373,6 +373,9 @@ void NanmedianGradInferMeta(const MetaTensor& x,
                             const std::string& mode,
                             MetaTensor* x_grad);
 
+void PartialConcatGradInferMeta(const std::vector<const MetaTensor*>& xs,
+                                std::vector<MetaTensor*> x_grads);
+
 void NceGradInferMeta(const MetaTensor& input,
                       const MetaTensor& bias,
                       const MetaTensor& weight,

paddle/phi/infermeta/unary.cc

@@ -4480,6 +4480,77 @@ void SumInferMeta(const MetaTensor& x,
   SumRawInferMeta(x, axis, keep_dim, reduce_all, dtype, out, config);
 }
 
+void PartialConcatInferMeta(const std::vector<const MetaTensor*>& xs,
+                            int start_index,
+                            int length,
+                            MetaTensor* out,
+                            MetaConfig config) {
+  int64_t batch_size = -1;
+  int64_t input_len = -1;
+
+  auto inputs_num = xs.size();
+  PADDLE_ENFORCE_GT(inputs_num,
+                    0,
+                    phi::errors::InvalidArgument(
+                        "ShapeError: Input tensors count should > 0. But "
+                        "received inputs' length is 0."));
+
+  // Only support two dimensions now, should be extended later
+  // when length is -1, need make sure all dimensions to be added are the same
+  for (size_t i = 0; i < inputs_num; i++) {
+    auto x_dim = xs[i]->dims();
+
+    PADDLE_ENFORCE_EQ(
+        x_dim.size(),
+        2,
+        phi::errors::InvalidArgument("Only support two dimensions input now."));
+
+    if (i == 0) {
+      batch_size = x_dim[0];
+      input_len = x_dim[1];
+    } else {
+      // each tensor's dim must eq
+      PADDLE_ENFORCE_EQ(x_dim[0],
+                        batch_size,
+                        phi::errors::InvalidArgument(
+                            "The batch size of all inputs must be same"));
+      PADDLE_ENFORCE_EQ(x_dim[1],
+                        input_len,
+                        phi::errors::InvalidArgument(
+                            "The input len of all inputs must be same"));
+    }
+  }
+
+  PADDLE_ENFORCE_EQ(
+      start_index >= -input_len && start_index < input_len,
+      true,
+      phi::errors::InvalidArgument(
+          "The start_index is expected to be in range of [%d, %d), but got %d",
+          -input_len,
+          input_len,
+          start_index));
+
+  if (start_index < 0) {
+    start_index += input_len;
+  }
+
+  if (length > 0) {
+    PADDLE_ENFORCE_GE(input_len,
+                      start_index + length,
+                      phi::errors::OutOfRange(
+                          "start_index + length is larger than input length"));
+  }
+
+  std::vector<int64_t> out_dims(2);
+  out_dims[0] = batch_size;
+  // colnum = input_num * length
+  out_dims[1] = (length < 0) ? input_len - start_index : length;
+  out_dims[1] *= inputs_num;
+  DDim out_dim = common::make_ddim(out_dims);
+  out->set_dims(out_dim);
+  out->set_dtype(xs[0]->dtype());
+}
+
 void SvdInferMeta(const MetaTensor& x,
                   bool full_matrices,
                   MetaTensor* u,

paddle/phi/infermeta/unary.h

@@ -705,6 +705,12 @@ void SumRawInferMeta(const MetaTensor& x,
                      MetaTensor* out,
                      MetaConfig config = MetaConfig());
 
+void PartialConcatInferMeta(const std::vector<const MetaTensor*>& xs,
+                            int start_index,
+                            int length,
+                            MetaTensor* out,
+                            MetaConfig config = MetaConfig());
+
 void SvdInferMeta(const MetaTensor& x,
                   bool full_matrices,
                   MetaTensor* u,

test/white_list/pir_op_test_white_list

@@ -201,6 +201,7 @@ test_one_hot_v2_op
 test_one_hot_v2_op_static_build
 test_overlap_add_op
 test_pad3d_op
+test_partial_concat_op
 test_pass_quantization
 test_pixel_shuffle_op
 test_poisson_op