Fix typos epislon epsilon (#67404)

Author: co63oc

cmake/generic.cmake

@@ -562,7 +562,7 @@ function(cc_test_old TARGET_NAME)
     cmake_parse_arguments(cc_test "${options}" "${oneValueArgs}"
                           "${multiValueArgs}" ${ARGN})
     cc_test_build(${TARGET_NAME} SRCS ${cc_test_SRCS} DEPS ${cc_test_DEPS})
-    # we donot test hcom op, because it need complex configuration
+    # we do not test hcom op, because it need complex configuration
     # with more than one machine
     cc_test_run(${TARGET_NAME} COMMAND ${TARGET_NAME} ARGS ${cc_test_ARGS})
   elseif(WITH_TESTING AND NOT TEST ${TARGET_NAME})

test/cpp/inference/api/CMakeLists.txt

@@ -1,5 +1,5 @@
 # In Windows, c_api test link must link both 2 shared to avoid symbols redefinition,
-# in Linux, c_api test cant do like this or graph_to_program register more than once.
+# in Linux, c_api test can't do like this or graph_to_program register more than once.
 # Both Windows and Linux can only use paddle_inference_c, but this will increase size
 # of build folder by 30G.
 set(inference_api_tester_deps paddle_inference_api analysis_config)

test/cpp/inference/api/tester_helper.h

@@ -389,7 +389,7 @@ void SetFakeImageInput(std::vector<std::vector<PaddleTensor>> *inputs,
                        std::string model_filename = "model",
                        std::string params_filename = "params",
                        const std::vector<std::string> *feed_names = nullptr,
-                       const int continuous_inuput_index = 0) {
+                       const int continuous_input_index = 0) {
   // Set fake_image_data
   PADDLE_ENFORCE_EQ(FLAGS_test_all_data,
                     0,
@@ -442,7 +442,7 @@ void SetFakeImageInput(std::vector<std::vector<PaddleTensor>> *inputs,
     // fill input data, for profile easily, do not use random data here.
     for (size_t j = 0; j < len; ++j) {
       *(input_data + j) =
-          static_cast<float>((j + continuous_inuput_index) % len) / len;
+          static_cast<float>((j + continuous_input_index) % len) / len;
     }
   }
   (*inputs).emplace_back(input_slots);

test/cpp/inference/infer_ut/test_ernie_xnli_int8.cc

@@ -64,10 +64,10 @@ std::shared_ptr<Predictor> InitPredictor() {
   // only kHalf supported
   config.EnableTensorRtEngine(
       1 << 30, 1, 5, Config::Precision::kInt8, false, false);
-  // erinie varlen must be used with dynamic shape
+  // ernie varlen must be used with dynamic shape
   config.SetTRTDynamicShapeInfo(
       min_input_shape, max_input_shape, opt_input_shape);
-  // erinie varlen must be used with oss
+  // ernie varlen must be used with oss
   config.EnableVarseqlen();
   paddle_infer::experimental::InternalUtils::SetTransformerPosid(&config,
                                                                  input_name2);

test/cpp/inference/infer_ut/test_suite.h

@@ -149,7 +149,7 @@ void SingleThreadPrediction(paddle_infer::Predictor *predictor,
 
 void CompareRecord(std::map<std::string, Record> *truth_output_data,
                    std::map<std::string, Record> *infer_output_data,
-                   float epislon = 1e-5) {
+                   float epsilon = 1e-5) {
   for (const auto &[key, value] : *infer_output_data) {
     auto truth_record = (*truth_output_data)[key];
     VLOG(1) << "output name: " << key;
@@ -159,7 +159,7 @@ void CompareRecord(std::map<std::string, Record> *truth_output_data,
       VLOG(1) << "compare: " << value.data.data()[i] << ",\t"
               << truth_record.data.data()[i];
       ASSERT_LT(fabs(value.data.data()[i] - truth_record.data.data()[i]),
-                epislon);
+                epsilon);
     }
   }
 }

test/deprecated/legacy_test/test_lbfgs_deprecated.py

@@ -131,7 +131,7 @@ def func(position):
             # minimum = (a, a^2)
             x, y = position[0], position[1]
             c = (a - x) ** 2 + b * (y - x**2) ** 2
-            # the return cant be np array[1], or in jacobin will cause flat error
+            # the return can't be np array[1], or in jacobin will cause flat error
             return c[0]
 
         x0 = np.random.random(size=[2]).astype('float32')

test/prim/prim/vjp/eager/test_comp_eager_index_add_double_grad.py

@@ -27,7 +27,7 @@
             np.random.randn(4, 3, 2),  # x
             np.random.randint(-3, 3, size=(16,)),  # index
             1,  # axis
-            np.random.randint(0, 3, size=(4, 16, 2)),  # valie
+            np.random.randint(0, 3, size=(4, 16, 2)),  # value
             np.random.rand(4, 3, 2),  # cotangent
             np.float32,  # dtype
         ),