tensor_map.mlir.in

// RUN: infrtexec -i %s | FileCheck %s

func @load_tensor_map() {
  %map = dt.load_params(){path="@CMAKE_BINARY_DIR@/multi_fc_model"}
  %size = dt.tensor_map_get_size(%map) -> i32
  infrt.print.i32 %size

  %a = dt.tensor_map_get_tensor(%map) {name="fc_bias"} -> !infrt.dense_tensor<CPU, FP32, NCHW>

  // CHECK: tensor: shape=shape[2], values=[0, 0]
  dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)

  infrt.return
}

func @load_phi_tensor_map() {
  %map = phi_dt.load_params(){path="@CMAKE_BINARY_DIR@/multi_fc_model"}
  %size = phi_dt.tensor_map_get_size(%map) -> i32
  infrt.print.i32 %size

  %a = phi_dt.tensor_map_get_tensor(%map) {name="fc_bias"} -> !infrt.dense_tensor<CPU, FP32, NCHW>

  // CHECK: dense_tensor: shape=shape[2], value=[0,0]
  phi_dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)

  infrt.return
}

func @load_combined_phi_tensor_map() {
  %map = phi_dt.load_combined_params(){model_path="@CMAKE_BINARY_DIR@/multi_fc_model/fc.pdmodel",
    params_path="@CMAKE_BINARY_DIR@/multi_fc_model/fc.pdiparams"}
  %size = phi_dt.tensor_map_get_size(%map) -> i32
  infrt.print.i32 %size

  %a = phi_dt.tensor_map_get_tensor(%map) {name="fc_bias"} -> !infrt.dense_tensor<CPU, FP32, NCHW>

  // CHECK: dense_tensor: shape=shape[2], value=[0,0]
  phi_dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)

  infrt.return
}