Internal change

PiperOrigin-RevId: 340146798
Change-Id: I22b6f23e305c21c7c84d1ad2c0f22ee6fbef1343

tensorflow/lite/testing/generated_examples_zip_test.cc

@@ -291,13 +291,10 @@ std::vector<string> UnarchiveAndFindTestNames(const string& zip_file,
 class OpsTest : public ::testing::TestWithParam<string> {};
 
 TEST_P(OpsTest, RunZipTests) {
-  string test_path_and_label = GetParam();
-  size_t end_pos = test_path_and_label.find(" ");
-  string test_path = test_path_and_label.substr(0, end_pos);
-  string label = test_path_and_label.substr(end_pos + 1);
+  string test_path = GetParam();
   string tflite_test_case = test_path + "_tests.txt";
   string tflite_dir = test_path.substr(0, test_path.find_last_of("/"));
-  string test_name = label.substr(label.find_last_of('/'));
+  string test_name = test_path.substr(test_path.find_last_of('/'));
 
   std::ifstream tflite_stream(tflite_test_case);
   ASSERT_TRUE(tflite_stream.is_open()) << tflite_test_case;
@@ -308,7 +305,7 @@ TEST_P(OpsTest, RunZipTests) {
 
   auto quantized_tests_error = GetQuantizeTestsError();
   bool fully_quantize = false;
-  if (label.find("fully_quantize=True") != std::string::npos) {
+  if (test_path.find("fully_quantize=True") != std::string::npos) {
     for (const auto& p : quantized_tests_error) {
       if (RE2::PartialMatch(test_name, p.first)) {
         test_driver.SetQuantizationErrorMultiplier(p.second);

tensorflow/lite/testing/op_tests/conv_activation.py

@@ -40,7 +40,6 @@ def make_conv_activation_tests(activation_op):
             "constant_filter": [True, False],
             "channel_multiplier": [1, 2],
             "fully_quantize": [False],
-            "quant_16x8": [False],
             "dynamic_range_quantize": [False],
         },
         # TODO(b/134702301): The fully_quantize param is just ignored by the
@@ -48,15 +47,14 @@ def make_conv_activation_tests(activation_op):
         # these tests or handle it properly in the mlir_convert() function.
         {
             "input_shape": [[1, 3, 4, 3], [4, 6, 6, 1]],
-            "filter_shape": [[1, 1], [2, 3]],
+            "filter_shape": [[1, 1], [2, 3], [3, 3]],
             "strides": [[1, 1, 1, 1], [1, 2, 3, 1]],
-            "dilations": [[1, 1, 1, 1], [1, 3, 2, 1]],
+            "dilations": [[1, 1, 1, 1], [1, 3, 2, 1], [1, 2, 2, 1]],
             "padding": ["SAME", "VALID"],
             "data_format": ["NHWC"],  # TODO(aselle): NCHW  would be good
             "constant_filter": [True],
             "channel_multiplier": [1, 2],
             "fully_quantize": [True],
-            "quant_16x8": [False, True],
             "dynamic_range_quantize": [False],
         },
         {
@@ -69,7 +67,6 @@ def make_conv_activation_tests(activation_op):
             "constant_filter": [True],
             "channel_multiplier": [1, 2],
             "fully_quantize": [False],
-            "quant_16x8": [False],
             "dynamic_range_quantize": [True],
         },
     ]
@@ -126,7 +123,7 @@ def make_conv_activation_tests(activation_op):
         test_parameters,
         build_graph,
         build_inputs,
-        expected_tf_failures=48)
+        expected_tf_failures=60)
 
   return f
 

tensorflow/lite/testing/zip_test_utils.py

@@ -342,7 +342,6 @@ def make_zip_of_tests(options,
   if options.multi_gen_state:
     label_base_path = options.multi_gen_state.label_base_path
 
-  i = 1
   for parameters in test_parameters:
     keys = parameters.keys()
     for curr in itertools.product(*parameters.values()):
@@ -350,8 +349,6 @@ def make_zip_of_tests(options,
           "%s=%r" % z for z in sorted(zip(keys, curr))).replace(" ", ""))
       if label[0] == "/":
         label = label[1:]
-      zip_path_label = label_base_path.replace(".zip", "_") + str(i)
-      i += 1
       if label in processed_labels:
         # Do not populate data for the same label more than once. It will cause
         # errors when unzipping.
@@ -400,14 +397,13 @@ def make_zip_of_tests(options,
 
         return input_values, output_values
 
-      def build_example(label, param_dict_real, zip_path_label):
+      def build_example(label, param_dict_real):
         """Build the model with parameter values set in param_dict_real.
 
         Args:
-          label: Label of the model
+          label: Label of the model (i.e. the filename in the zip).
           param_dict_real: Parameter dictionary (arguments to the factories
             make_graph and make_test_inputs)
-          zip_path_label: Filename in the zip
 
         Returns:
           (tflite_model_binary, report) where tflite_model_binary is the
@@ -470,7 +466,7 @@ def make_zip_of_tests(options,
         report["toco_log"] = toco_log
 
         if options.save_graphdefs:
-          archive.writestr(zip_path_label + ".pbtxt",
+          archive.writestr(label + ".pbtxt",
                            text_format.MessageToString(graph_def),
                            zipfile.ZIP_DEFLATED)
 
@@ -479,25 +475,25 @@ def make_zip_of_tests(options,
             # Set proper min max values according to input dtype.
             baseline_inputs, baseline_outputs = generate_inputs_outputs(
                 tflite_model_binary, min_value=0, max_value=255)
-          archive.writestr(zip_path_label + ".bin", tflite_model_binary,
+          archive.writestr(label + ".bin", tflite_model_binary,
                            zipfile.ZIP_DEFLATED)
           example = {"inputs": baseline_inputs, "outputs": baseline_outputs}
 
           example_fp = StringIO()
           write_examples(example_fp, [example])
-          archive.writestr(zip_path_label + ".inputs", example_fp.getvalue(),
+          archive.writestr(label + ".inputs", example_fp.getvalue(),
                            zipfile.ZIP_DEFLATED)
 
           example_fp2 = StringIO()
-          write_test_cases(example_fp2, zip_path_label + ".bin", [example])
-          archive.writestr(zip_path_label + "_tests.txt",
-                           example_fp2.getvalue(), zipfile.ZIP_DEFLATED)
+          write_test_cases(example_fp2, label + ".bin", [example])
+          archive.writestr(label + "_tests.txt", example_fp2.getvalue(),
+                           zipfile.ZIP_DEFLATED)
 
-          zip_manifest.append(zip_path_label + " " + label + "\n")
+          zip_manifest.append(label + "\n")
 
         return tflite_model_binary, report
 
-      _, report = build_example(label, param_dict, zip_path_label)
+      _, report = build_example(label, param_dict)
 
       if report["toco"] == report_lib.FAILED:
         ignore_error = False