Merge pull request apache#2 from weberlo/tutorial-2

Add components for tutorial 3

include/tvm/runtime/crt/platform.h

@@ -37,6 +37,24 @@ extern "C" {
  */
 void __attribute__((noreturn)) TVMPlatformAbort(int code);
 
+/*! \brief Start a device timer.
+ *
+ * The device timer used must not be running.
+ *
+ * \return An error code.
+ */
+int TVMPlatformTimerStart();
+
+/*! \brief Stop the running device timer and get the elapsed time (in microseconds).
+ *
+ * The device timer used must be running.
+ *
+ * \param res_us Pointer to write elapsed time into.
+ *
+ * \return An error code.
+ */
+int TVMPlatformTimerStop(double* res_us);
+
 #ifdef __cplusplus
 }  // extern "C"
 #endif

python/tvm/contrib/debugger/debug_runtime.py

@@ -30,7 +30,7 @@
 _DUMP_PATH_PREFIX = "_tvmdbg_"
 
 
-def create(graph_json_str, libmod, ctx, dump_root=None):
+def create(graph_json_str, libmod, ctx, dump_root=None, number=10, repeat=1, min_repeat_ms=1):
     """Create a runtime executor module given a graph and module.
 
     Parameters
@@ -72,7 +72,8 @@ def create(graph_json_str, libmod, ctx, dump_root=None):
             "config.cmake and rebuild TVM to enable debug mode"
         )
     func_obj = fcreate(graph_json_str, libmod, *device_type_id)
-    return GraphModuleDebug(func_obj, ctx, graph_json_str, dump_root)
+    return GraphModuleDebug(func_obj, ctx, graph_json_str, dump_root,
+        number=number, repeat=repeat, min_repeat_ms=min_repeat_ms)
 
 
 class GraphModuleDebug(graph_runtime.GraphModule):
@@ -99,13 +100,17 @@ class GraphModuleDebug(graph_runtime.GraphModule):
         None will make a temp folder in /tmp/tvmdbg<rand_string> and does the dumping
     """
 
-    def __init__(self, module, ctx, graph_json_str, dump_root):
+    def __init__(self, module, ctx, graph_json_str, dump_root,
+            number, repeat, min_repeat_ms):
         self._dump_root = dump_root
         self._dump_path = None
         self._get_output_by_layer = module["get_output_by_layer"]
         self._run_individual = module["run_individual"]
         graph_runtime.GraphModule.__init__(self, module)
         self._create_debug_env(graph_json_str, ctx)
+        self.number = number
+        self.repeat = repeat
+        self.min_repeat_ms = min_repeat_ms
 
     def _format_context(self, ctx):
         return str(ctx[0]).upper().replace("(", ":").replace(")", "")
@@ -180,7 +185,8 @@ def _run_debug(self):
 
         """
         self.debug_datum._time_list = [
-            [float(t) * 1e-6] for t in self.run_individual(10, 1, 1)
+            [float(t) * 1e-6] for t in
+            self.run_individual(self.number, self.repeat, self.min_repeat_ms)
         ]
         for i, node in enumerate(self.debug_datum.get_graph_nodes()):
             num_outputs = self.debug_datum.get_graph_node_output_num(node)

python/tvm/micro/__init__.py

@@ -17,7 +17,7 @@
 """MicroTVM module for bare-metal backends"""
 
 from .artifact import Artifact
-from .build import build_static_runtime, DefaultOptions, TVM_ROOT_DIR, Workspace
+from .build import build_static_runtime, DefaultOptions, TVM_ROOT_DIR, CRT_ROOT_DIR, Workspace
 from .compiler import Compiler, DefaultCompiler, Flasher
 from .debugger import GdbRemoteDebugger, RpcDebugger
 from .micro_library import MicroLibrary

python/tvm/relay/analysis/analysis.py

@@ -21,6 +21,9 @@
 configuring the passes and scripting them in Python.
 """
 from tvm.ir import IRModule
+# TODO(weberlo) remove when we port dtype collectors to C++
+from tvm.relay.expr_functor import ExprVisitor
+from tvm.relay.type_functor import TypeVisitor
 
 from . import _ffi_api
 from .feature import Feature
@@ -219,6 +222,50 @@ def all_type_vars(expr, mod=None):
     return _ffi_api.all_type_vars(expr, use_mod)
 
 
+class TyDtypeCollector(TypeVisitor):
+    """Pass that collects data types used in the visited type."""
+
+    def __init__(self):
+        TypeVisitor.__init__(self)
+        self.dtypes = set()
+
+    def visit_tensor_type(self, tt):
+        self.dtypes.add(tt.dtype)
+
+
+class ExprDtypeCollector(ExprVisitor):
+    """Pass that collects data types used in all types in the visited expression."""
+
+    def __init__(self):
+        ExprVisitor.__init__(self)
+        self.ty_visitor = TyDtypeCollector()
+
+    def visit(self, expr):
+        if hasattr(expr, 'checked_type'):
+            self.ty_visitor.visit(expr.checked_type)
+        elif hasattr(expr, 'type_annotation'):
+            self.ty_visitor.visit(expr.type_annotation)
+        ExprVisitor.visit(self, expr)
+
+
+def all_dtypes(expr):
+    """Collect set of all data types used in `expr`.
+
+    Parameters
+    ----------
+    expr : tvm.relay.Expr
+        The input expression
+
+    Returns
+    -------
+    ret : Set[String]
+        Set of data types used in the expression
+    """
+    dtype_collector = ExprDtypeCollector()
+    dtype_collector.visit(expr)
+    return dtype_collector.ty_visitor.dtypes
+
+
 def collect_device_info(expr):
     """Collect the device allocation map for the given expression. The device
     ids are propagated from the `device_copy` operators.