Merge branch 'check_model_configs' into 'master'

Check model configs

See merge request !458

mace/kernels/opencl/cl/common.h

@@ -32,8 +32,8 @@
 #define CHECK_OUT_OF_RANGE_FOR_IMAGE2D(image, coord)
 #endif
 
-#define READ_IMAGET(image, coord, value) \
-  CMD_TYPE(read_image, CMD_DATA_TYPE)(image, coord, value)
+#define READ_IMAGET(image, sampler, coord) \
+  CMD_TYPE(read_image, CMD_DATA_TYPE)(image, sampler, coord)
 #define WRITE_IMAGET(image, coord, value)        \
   CHECK_OUT_OF_RANGE_FOR_IMAGE2D(image, coord)   \
   CMD_TYPE(write_image, CMD_DATA_TYPE)(image, coord, value);

mace/python/tools/converter.py

@@ -175,7 +175,10 @@ def parse_args():
     parser.add_argument(
         "--platform", type=str, default="tensorflow", help="tensorflow/caffe")
     parser.add_argument(
-        "--embed_model_data", type=str2bool, default=True, help="input shape.")
+        "--embed_model_data",
+        type=str2bool,
+        default=True,
+        help="embed model data.")
     return parser.parse_known_args()
 
 

tools/mace_tools.py

@@ -336,8 +336,74 @@ def str_to_caffe_env_type(v):
 
 
 def parse_model_configs():
+    print("============== Load and Parse configs ==============")
     with open(FLAGS.config) as f:
         configs = yaml.load(f)
+        target_abis = configs.get("target_abis", [])
+        if not isinstance(target_abis, list) or not target_abis:
+            print("CONFIG ERROR:")
+            print("target_abis list is needed!")
+            print("For example: 'target_abis: [armeabi-v7a, arm64-v8a]'")
+            exit(1)
+
+        embed_model_data = configs.get("embed_model_data", "")
+        if embed_model_data == "" or not isinstance(embed_model_data, int) or \
+                embed_model_data < 0 or embed_model_data > 1:
+            print("CONFIG ERROR:")
+            print("embed_model_data must be integer in range [0, 1]")
+            exit(1)
+
+        model_names = configs.get("models", "")
+        if not model_names:
+            print("CONFIG ERROR:")
+            print("models attribute not found in config file")
+            exit(1)
+
+        for model_name in model_names:
+            model_config = configs["models"][model_name]
+            platform = model_config.get("platform", "")
+            if platform == "" or platform not in ["tensorflow", "caffe"]:
+                print("CONFIG ERROR:")
+                print("'platform' must be 'tensorflow' or 'caffe'")
+                exit(1)
+
+            for key in ["model_file_path", "model_sha256_checksum",
+                        "runtime"]:
+                value = model_config.get(key, "")
+                if value == "":
+                    print("CONFIG ERROR:")
+                    print("'%s' is necessary" % key)
+                    exit(1)
+
+            for key in ["input_nodes", "input_shapes", "output_nodes",
+                        "output_shapes"]:
+                value = model_config.get(key, "")
+                if value == "":
+                    print("CONFIG ERROR:")
+                    print("'%s' is necessary" % key)
+                    exit(1)
+                if not isinstance(value, list):
+                    model_config[key] = [value]
+
+            for key in ["limit_opencl_kernel_time", "dsp_mode", "obfuscate",
+                        "fast_conv"]:
+                value = model_config.get(key, "")
+                if value == "":
+                    model_config[key] = 0
+                    print("'%s' for %s is set to default value: 0" %
+                          (key, model_name))
+
+            validation_inputs_data = model_config.get("validation_inputs_data",
+                                                      [])
+            model_config["validation_inputs_data"] = validation_inputs_data
+            if not isinstance(validation_inputs_data, list):
+                model_config["validation_inputs_data"] = [
+                        validation_inputs_data]
+
+            weight_file_path = model_config.get("weight_file_path", "")
+            model_config["weight_file_path"] = weight_file_path
+
+        print("Parse model configs successfully!\n")
         return configs
 
 
@@ -434,16 +500,10 @@ def process_models(project_name, configs, embed_model_data, vlog_level,
     for model_name in configs["models"]:
         print '===================', model_name, '==================='
         model_config = configs["models"][model_name]
-        input_file_list = model_config.get("validation_inputs_data",
-                                           [])
+        input_file_list = model_config["validation_inputs_data"]
         data_type, device_type = get_data_and_device_type(
                 model_config["runtime"])
 
-        for key in ["input_nodes", "output_nodes", "input_shapes",
-                    "output_shapes"]:
-            if not isinstance(model_config[key], list):
-                model_config[key] = [model_config[key]]
-
         # Create model build directory
         model_path_digest = md5sum(model_config["model_file_path"])
 
@@ -472,7 +532,7 @@ def process_models(project_name, configs, embed_model_data, vlog_level,
         model_file_path, weight_file_path = get_model_files(
                 model_config["model_file_path"],
                 model_output_dir,
-                model_config.get("weight_file_path", ""))
+                model_config["weight_file_path"])
 
         if FLAGS.mode == "build" or FLAGS.mode == "run" or \
                 FLAGS.mode == "validate" or \
@@ -604,8 +664,7 @@ def process_models(project_name, configs, embed_model_data, vlog_level,
         if os.path.exists(throughput_test_output_dir):
             sh.rm("-rf", throughput_test_output_dir)
         os.makedirs(throughput_test_output_dir)
-        input_file_list = model_config.get("validation_inputs_data",
-                                           [])
+        input_file_list = model_config["validation_inputs_data"]
         sh_commands.gen_random_input(throughput_test_output_dir,
                                      first_model["input_nodes"],
                                      first_model["input_shapes"],
@@ -654,7 +713,7 @@ def main(unused_args):
 
     target_socs = get_target_socs(configs)
 
-    embed_model_data = configs.get("embed_model_data", 1)
+    embed_model_data = configs["embed_model_data"]
     vlog_level = FLAGS.vlog_level
     phone_data_dir = "/data/local/tmp/mace_run/"
     for target_abi in configs["target_abis"]: