Fix lint warning (#3)

nnvm/include/nnvm/op_attr_types.h

@@ -224,7 +224,7 @@ using FCorrectLayout = std::function<bool(
  * \return success flag.
  */
 using FCorrectLayoutEx = std::function<bool(
-    NodeAttrs& attrs,
+    const NodeAttrs& attrs,
     std::vector<TShape>* ishapes,
     std::vector<Layout>* ilayouts,
     const std::vector<Layout>* last_ilayouts,

nnvm/python/nnvm/frontend/mxnet.py

@@ -274,8 +274,8 @@ def _lrn(inputs, attrs):
     return _get_nnvm_op(op_name)(*inputs, **new_attrs)
 
 def _symbol_ring_buffer(inputs, attrs):
-  output = _get_nnvm_op('ring_buffer')(*inputs, **attrs)
-  return _sym._assign(inputs[1], output)
+    output = _get_nnvm_op('ring_buffer')(*inputs, **attrs)
+    return _sym._assign(inputs[1], output)
 
 
 def _copy(inputs, _):
@@ -365,8 +365,7 @@ def _argmin(inputs, attrs):
     'expand_dims'   : _expand_dims,
     'LRN'           : _lrn,
     'ring_buffer'   : _symbol_ring_buffer,
-    'LinearRegressionOutput' : _copy,
-    'argmax'                 : _argmax
+    'LinearRegressionOutput' : _copy
 }
 
 def _convert_symbol(op_name, inputs, attrs,

nnvm/python/nnvm/top/nn.py

@@ -121,12 +121,12 @@ def compute_conv2d(attrs, inputs, _):
     else:
         raise ValueError("not support arbitrary group number for now")
 
-        if attrs.get_bool("use_bias"):
-            bias = inputs[2]
-            expand_axis = 1 if layout == "NCHW" else 0
-            bias = topi.expand_dims(bias, axis=expand_axis, num_newaxis=2)
-            out = topi.add(out, bias)
-        return out
+    if attrs.get_bool("use_bias"):
+        bias = inputs[2]
+        expand_axis = 1 if layout == "NCHW" else 0
+        bias = topi.expand_dims(bias, axis=expand_axis, num_newaxis=2)
+        out = topi.add(out, bias)
+    return out
 
 @reg.register_schedule("conv2d")
 def schedule_conv2d(attrs, outs, target):
@@ -260,11 +260,11 @@ def compute_contrib_conv2d_winograd_without_weight_transform(attrs, inputs, _):
         inputs[0], inputs[1], strides, padding, dilation, layout, out_dtype,
         tile_size)
 
-        if attrs.get_bool("use_bias"):
-            bias = inputs[2]
-            bias = topi.expand_dims(bias, axis=1, num_newaxis=2)
-            out = topi.add(out, bias)
-        return out
+    if attrs.get_bool("use_bias"):
+        bias = inputs[2]
+        bias = topi.expand_dims(bias, axis=1, num_newaxis=2)
+        out = topi.add(out, bias)
+    return out
 
 @reg.register_schedule("_contrib_conv2d_winograd_without_weight_transform")
 def schedule_contrib_conv2d_winograd_without_weight_transform(attrs, outs, target):
@@ -312,22 +312,22 @@ def schedule_conv2d_transpose(attrs, outs, target):
 reg.register_pattern("conv2d_transpose", OpPattern.OUT_ELEMWISE_FUSABLE)
 
 @reg.register_alter_op_layout("max_pool2d")
-def alter_pooling_layout(attrs, inputs, tinfos):
+def alter_pooling_layout_max_pool2d(attrs, inputs, tinfos):
     with tvm.target.create(attrs.get_string("target")):
         return topi.nn.max_pool2d_alter_layout(attrs, inputs, tinfos)
 
 @reg.register_alter_op_layout("avg_pool2d")
-def alter_pooling_layout(attrs, inputs, tinfos):
+def alter_pooling_layout_avg_pool2d(attrs, inputs, tinfos):
     with tvm.target.create(attrs.get_string("target")):
         return topi.nn.avg_pool2d_alter_layout(attrs, inputs, tinfos)
 
 @reg.register_alter_op_layout("global_max_pool2d")
-def alter_pooling_layout(attrs, inputs, tinfos):
+def alter_pooling_layout_global_max_pool2d(attrs, inputs, tinfos):
     with tvm.target.create(attrs.get_string("target")):
         return topi.nn.global_max_pool2d_alter_layout(attrs, inputs, tinfos)
 
 @reg.register_alter_op_layout("global_avg_pool2d")
-def alter_pooling_layout(attrs, inputs, tinfos):
+def alter_pooling_layout_global_avg_pool2d(attrs, inputs, tinfos):
     with tvm.target.create(attrs.get_string("target")):
         return topi.nn.global_avg_pool2d_alter_layout(attrs, inputs, tinfos)
 

nnvm/src/pass/graph_annotate.h

@@ -3,38 +3,38 @@
  * \file graph_annotate.h
  * \brief Define rules to annotate a graph.
  */
- #ifndef NNVM_PASS_GRAPH_ANNOTATE_H_
- #define NNVM_PASS_GRAPH_ANNOTATE_H_
+#ifndef NNVM_PASS_GRAPH_ANNOTATE_H_
+#define NNVM_PASS_GRAPH_ANNOTATE_H_
 
- #include <nnvm/graph.h>
+#include <nnvm/graph.h>
 
- #include <string>
- #include <unordered_map>
+#include <string>
+#include <unordered_map>
 
- namespace nnvm {
+namespace nnvm {
 
- class ManualAnnotator;
+class ManualAnnotator;
  /*
   * This class is an abstract class that can be derived by other classes to
   * implement how a node should be selected.
   */
- class GraphAnnotator {
-  public:
-   explicit GraphAnnotator(int fallback_device)
+class GraphAnnotator {
+ public:
+  explicit GraphAnnotator(int fallback_device)
        : fallback_device_(fallback_device) {}
-   virtual ~GraphAnnotator() = default;
-   // A virtual function that is implemented by different annotation methods.
-   virtual int AnnotateNode(const nnvm::Node* n) const = 0;
+  virtual ~GraphAnnotator() = default;
+  // A virtual function that is implemented by different annotation methods.
+  virtual int AnnotateNode(const nnvm::Node* n) const = 0;
 
-   int GetFallbackDevice() const {
+  int GetFallbackDevice() const {
      return fallback_device_;
-   }
+  }
 
-  private:
-   friend ManualAnnotator;
-   /* The fallback device. */
-   int fallback_device_;
- };
+ private:
+  friend ManualAnnotator;
+  /* The fallback device. */
+  int fallback_device_;
+};
 
  /*
   * This class defines a manual way to annotate a graph node. In this method,
@@ -43,28 +43,28 @@
   * is registered with a fallback property or the operator name has not been
   * saved, this node will be annotated with the fallback device.
   */
- class ManualAnnotator : public GraphAnnotator {
-   using OpNameDeviceMap = std::unordered_map<std::string, int>;
-  public:
-   explicit ManualAnnotator(const OpNameDeviceMap& op_name_dev_map,
+class ManualAnnotator : public GraphAnnotator {
+  using OpNameDeviceMap = std::unordered_map<std::string, int>;
+ public:
+  explicit ManualAnnotator(const OpNameDeviceMap& op_name_dev_map,
                             int fallback_device)
        : GraphAnnotator(fallback_device),
          op_name_dev_map_(new OpNameDeviceMap(op_name_dev_map)) {}
 
-   int AnnotateNode(const nnvm::Node* n) const final {
+  int AnnotateNode(const nnvm::Node* n) const final {
      if (n->is_variable()) return 0;
      if (n->op()->fallback) return fallback_device_;
 
      return op_name_dev_map_->count(n->op()->name)
                 ? op_name_dev_map_->at(n->op()->name)
                 : fallback_device_;
-   }
+  }
 
-  private:
-   std::unique_ptr<const OpNameDeviceMap> op_name_dev_map_;
- };
+ private:
+  std::unique_ptr<const OpNameDeviceMap> op_name_dev_map_;
+};
 
- using ManualAnnotatorPtr = std::shared_ptr<ManualAnnotator>;
+using ManualAnnotatorPtr = std::shared_ptr<ManualAnnotator>;
 
- }  // namespace nnvm
- #endif  // NNVM_PASS_GRAPH_ANNOTATE_H_
+}  // namespace nnvm
+#endif  // NNVM_PASS_GRAPH_ANNOTATE_H_

nnvm/src/top/nn/nn.cc

@@ -194,7 +194,7 @@ inline bool BatchNormInferShape(const nnvm::NodeAttrs& attrs,
   return true;
 }
 
-inline bool BatchNormCorrectLayout(NodeAttrs& attrs,
+inline bool BatchNormCorrectLayout(const NodeAttrs& attrs,
                                    std::vector<TShape>* ishapes,
                                    std::vector<Layout> *in_layouts,
                                    const std::vector<Layout> *last_in_layouts,
@@ -593,7 +593,7 @@ inline bool PadInferShape(const nnvm::NodeAttrs& attrs,
   return true;
 }
 
-inline bool PadCorrectLayout(NodeAttrs& attrs,
+inline bool PadCorrectLayout(const NodeAttrs& attrs,
                              std::vector<TShape>* ishapes,
                              std::vector<Layout>* ilayouts,
                              const std::vector<Layout>* last_ilayouts,

nnvm/src/top/tensor/broadcast.cc

@@ -129,7 +129,7 @@ inline bool BinaryBroadcastShape(const nnvm::NodeAttrs& attrs,
   return true;
 }
 
-inline bool BinaryBroadcastCorrectLayout(NodeAttrs& attrs,
+inline bool BinaryBroadcastCorrectLayout(const NodeAttrs& attrs,
                                          std::vector<TShape>* ishapes,
                                          std::vector<Layout>* ilayouts,
                                          const std::vector<Layout>* last_ilayouts,

python/tvm/ndarray.py

@@ -7,6 +7,7 @@
 from __future__ import absolute_import as _abs
 import numpy as _np
 
+from ._ffi.function import register_func
 from ._ffi.ndarray import TVMContext, TVMType, NDArrayBase
 from ._ffi.ndarray import context, empty, from_dlpack
 from ._ffi.ndarray import _set_class_ndarray
@@ -199,7 +200,6 @@ def array(arr, ctx=cpu(0)):
     return empty(arr.shape, arr.dtype, ctx).copyfrom(arr)
 
 
-from ._ffi.function import register_func
 @register_func("tvm.nd.random_uniform")
 def random_uniform(size, dtype, target):
     size = [int(x) for x in size.split()]

src/contrib/subgraph/tensorrt_executor.cc

@@ -9,13 +9,13 @@
 #include <dmlc/parameter.h>
 #include <dmlc/timer.h>
 #include <unordered_set>
+#include <cmath>
 #include <functional>
 #include <iostream>
 #include <sstream>
 #include "./subgraph.h"
 #include "./tensorrt_executor.h"
 #include "../../runtime/cuda/cuda_common.h"
-#include <cmath>
 
 namespace tvm {
 namespace contrib {

topi/python/topi/cuda/pooling.py

@@ -3,7 +3,6 @@
 import tvm
 from .. import tag
 from .. import generic
-from ..nn.pooling import *
 
 @generic.schedule_global_pool.register(["cuda", "gpu"])
 def schedule_global_pool(outs):

topi/python/topi/nn/pooling.py

@@ -1,8 +1,8 @@
 """TVM operator pooling compute."""
 from __future__ import absolute_import
+import tvm
 from .. import cpp
 
-import tvm
 
 POOL_TYPE_CODE = {
     "avg": 0,
@@ -102,6 +102,7 @@ def pool(data,
 
 @tvm.target.generic_func
 def max_pool2d_alter_layout(attrs, inputs, tinfos):
+    #pylint: disable=unused-argument
     """Change max pool2d layout.
 
     Parameters
@@ -119,6 +120,7 @@ def max_pool2d_alter_layout(attrs, inputs, tinfos):
 
 @tvm.target.generic_func
 def avg_pool2d_alter_layout(attrs, inputs, tinfos):
+    #pylint: disable=unused-argument
     """Change average pool2d layout.
 
     Parameters
@@ -136,6 +138,7 @@ def avg_pool2d_alter_layout(attrs, inputs, tinfos):
 
 @tvm.target.generic_func
 def global_max_pool2d_alter_layout(attrs, inputs, tinfos):
+    #pylint: disable=unused-argument
     """Change global max pool2d layout.
 
     Parameters
@@ -153,6 +156,7 @@ def global_max_pool2d_alter_layout(attrs, inputs, tinfos):
 
 @tvm.target.generic_func
 def global_avg_pool2d_alter_layout(attrs, inputs, tinfos):
+    #pylint: disable=unused-argument
     """Change global average pool2d layout.
 
     Parameters