/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include "tensorflow/core/framework/shape_inference_testutil.h"

#include <string>

#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/lib/strings/str_util.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace shape_inference {

namespace {

#define EXPECT_CONTAINS(str, substr)                              \
  do {                                                            \
    string s = (str);                                             \
    EXPECT_TRUE(absl::StrContains(s, substr)) << "String: " << s; \
  } while (false)

static OpShapeInferenceFn* global_fn_ptr = nullptr;
REGISTER_OP("OpOneOut")
    .Input("inputs: N * T")
    .Output("o1: T")
    .Attr("N: int >= 1")
    .Attr("T: numbertype")
    .SetShapeFn([](InferenceContext* c) { return (*global_fn_ptr)(c); });
REGISTER_OP("OpTwoOut")
    .Input("inputs: N * T")
    .Output("o1: T")
    .Output("o2: T")
    .Attr("N: int >= 1")
    .Attr("T: numbertype")
    .SetShapeFn([](InferenceContext* c) { return (*global_fn_ptr)(c); });

string RunInferShapes(const string& op_name, const string& ins,
                      const string& expected_outs, OpShapeInferenceFn fn) {
  ShapeInferenceTestOp op(op_name);
  const int num_inputs = 1 + std::count(ins.begin(), ins.end(), ';');
  std::vector<NodeDefBuilder::NodeOut> src_list;
  src_list.reserve(num_inputs);
  for (int i = 0; i < num_inputs; ++i) src_list.emplace_back("a", 0, DT_FLOAT);
  NodeDef node_def;
  TF_CHECK_OK(NodeDefBuilder("dummy", op_name)
                  .Input(src_list)
                  .Attr("N", num_inputs)
                  .Finalize(&op.node_def));
  global_fn_ptr = &fn;
  return std::string(
      ShapeInferenceTestutil::InferShapes(op, ins, expected_outs).message());
}

}  // namespace

TEST(ShapeInferenceTestutilTest, Failures) {
  auto fn_copy_input_0 = [](InferenceContext* c) {
    c->set_output(0, c->input(0));
    return absl::OkStatus();
  };
  auto fn_copy_input_2 = [](InferenceContext* c) {
    c->set_output(0, c->input(2));
    return absl::OkStatus();
  };
  auto fn_output_unknown_shapes = [](InferenceContext* c) {
    for (int i = 0; i < c->num_outputs(); ++i) {
      c->set_output(i, c->UnknownShape());
    }
    return absl::OkStatus();
  };
  auto fn_output_1_2 = [](InferenceContext* c) {
    c->set_output(0, c->Matrix(1, 2));
    return absl::OkStatus();
  };
  auto fn_output_u_2 = [](InferenceContext* c) {
    c->set_output(0, c->Matrix(InferenceContext::kUnknownDim, 2));
    return absl::OkStatus();
  };
  const string& op = "OpOneOut";

  EXPECT_EQ("Shape inference should have returned error",
            RunInferShapes(op, "[1];[2];[1]", "e", fn_copy_input_0));
  EXPECT_CONTAINS(RunInferShapes(op, "[1];[2];[1]", "[1];[2]", fn_copy_input_0),
                  "wrong number of outputs");
  auto s = ShapeInferenceTestutil::InferShapes(ShapeInferenceTestOp("NoSuchOp"),
                                               "", "");
  EXPECT_TRUE(
      absl::StartsWith(s.message(), "Op type not registered 'NoSuchOp'"));

  // Wrong shape error messages.
  EXPECT_CONTAINS(RunInferShapes(op, "[1];[2];[1]", "?", fn_copy_input_0),
                  "expected to not match");
  EXPECT_CONTAINS(RunInferShapes(op, "[1];[2];[1]", "in2", fn_copy_input_0),
                  "should have matched one of (in2)");
  EXPECT_CONTAINS(RunInferShapes(op, "[1];[2];[1]", "in1|in2", fn_copy_input_0),
                  "should have matched one of (in1|in2)");
  EXPECT_CONTAINS(RunInferShapes(op, "[1];[2];[1]", "[1]", fn_copy_input_2),
                  "but was expected to not match");
  EXPECT_CONTAINS(RunInferShapes(op, "[1];[2];[1]", "in0|in1", fn_output_1_2),
                  "Output 0 should have matched an input shape");
  EXPECT_EQ("Output 0 expected to be unknown. Output shape was [1,2]",
            RunInferShapes(op, "[1];[2];[1]", "?", fn_output_1_2));
  EXPECT_EQ("Output 0 expected rank 3 but was 2. Output shape was [1,2]",
            RunInferShapes(op, "[1];[2];[1]", "[1,2,3]", fn_output_1_2));
  EXPECT_EQ(
      "Output 0 expected rank 2 but was ?. Output shape was ?",
      RunInferShapes(op, "[1];[2];[1]", "[1,2]", fn_output_unknown_shapes));

  // Wrong shape error messages on the second output.
  EXPECT_EQ("Output 1 expected rank 3 but was ?. Output shape was ?",
            RunInferShapes("OpTwoOut", "[1];[2];[1]", "?;[1,2,3]",
                           fn_output_unknown_shapes));

  // Wrong dimension error messages.
  EXPECT_EQ("Output dim 0,1 expected to be 3 but was 2. Output shape was [1,2]",
            RunInferShapes(op, "[1];[2];[1]", "[1,3]", fn_output_1_2));
  EXPECT_EQ("Output dim 0,0 expected to be 2 but was 1. Output shape was [1,2]",
            RunInferShapes(op, "[1];[2];[1]", "[2,2]", fn_output_1_2));
  EXPECT_EQ(
      "Output dim 0,0 expected to be unknown but was 1. Output shape was [1,2]",
      RunInferShapes(op, "[1];[2];[1]", "[?,2]", fn_output_1_2));
  EXPECT_EQ("Output dim 0,1 expected to be 1 but was 2. Output shape was [?,2]",
            RunInferShapes(op, "[1];[2];[1]", "[?,1]", fn_output_u_2));
  EXPECT_EQ("Output dim 0,0 expected to be 1 but was ?. Output shape was [?,2]",
            RunInferShapes(op, "[0,1,?];[2];[1]", "[1,2]", fn_output_u_2));
  auto fn = [](InferenceContext* c) {
    c->set_output(0, c->MakeShape({c->Dim(c->input(0), 1), c->MakeDim(2),
                                   c->UnknownDim(), c->Dim(c->input(2), 0)}));
    return absl::OkStatus();
  };
  const string ins = "[0,1,?];[2];[1]";
  EXPECT_CONTAINS(RunInferShapes(op, ins, "[?,2,?,d2_0]", fn),
                  "Output dim 0,0 expected to be an unknown");
  EXPECT_CONTAINS(RunInferShapes(op, ins, "[0,2,?,d2_0]", fn),
                  "Output dim 0,0 expected to be 0 but matched input d0_1.");
  EXPECT_CONTAINS(
      RunInferShapes(op, ins, "[d0_0,2,?,d2_0]", fn),
      "dim 0,0 matched input d0_1, but should have matched one of (d0_0).");
  EXPECT_CONTAINS(RunInferShapes(op, ins, "[x,2,?,d2_0]", fn),
                  "Output dim 0,0: the expected dimension value 'x' failed to "
                  "parse as int64.");
  EXPECT_CONTAINS(RunInferShapes(op, ins, "[d0_0|d0_2,2,?,d2_0]", fn),
                  "dim 0,0 matched input d0_1, but should have matched one of "
                  "(d0_0|d0_2).");
  EXPECT_CONTAINS(RunInferShapes(op, ins, "[d0_1,?,?,d0_0|d2_0]", fn),
                  ("Output dim 0,1 expected to be unknown but was 2. "
                   "Output shape was [1,2,?,1]"));
  EXPECT_EQ(
      "Output dim 0,2 expected to be 8 but was ?. Output shape was [1,2,?,1]",
      RunInferShapes(op, ins, "[d0_1,2,8,d0_0|d2_0]", fn));
  EXPECT_CONTAINS(RunInferShapes(op, ins, "[d0_1,2,d0_1|d2_0,d0_0|d2_0]", fn),
                  "expected to match");
  EXPECT_EQ("",  // OK, no error.
            RunInferShapes(op, ins, "[d0_1,2,?,d0_0|d2_0]", fn));
}

}  // namespace shape_inference
}  // namespace tensorflow
