Fixed minor misspelling (#7499)

Co-authored-by: mshr-h <mshr-h@users.noreply.github.com>

include/tvm/ir/attrs.h

@@ -146,7 +146,7 @@ class BaseAttrsNode : public Object {
   virtual void VisitAttrs(AttrVisitor* v) {}
   /*!
    * \brief Initialize the attributes by sequence of arguments
-   * \param args The postional arguments in the form
+   * \param args The positional arguments in the form
    *        [key0, value0, key1, value1, ..., key_n, value_n]
    */
   template <typename... Args>

include/tvm/runtime/packed_func.h

@@ -1204,7 +1204,7 @@ struct func_signature_helper<R (T::*)(Args...) const> {
 
 /*!
  * \brief template class to get function signature of a function or functor.
- * \tparam T The funtion/functor type.
+ * \tparam T The function/functor type.
  */
 template <typename T>
 struct function_signature {

include/tvm/topi/einsum.h

@@ -439,7 +439,7 @@ inline std::vector<std::string> Split(const std::string& str, const std::string&
  * \param subscripts input subscripts.
  * \param operands operand tensors.
  *
- * \return vector of strings, vector[0] represents the input part, vector[1] represents the ouput.
+ * \return vector of strings, vector[0] represents the input part, vector[1] represents the output.
  * if no output, the vector[1] is NULL.
  * "ab, bc -> ac" => ["ab,bc", "ac"]
  */

nnvm/src/core/symbolic.cc

@@ -240,7 +240,7 @@ std::vector<std::string> Symbol::ListInputNames(ListInputOption option) const {
 }
 
 std::vector<std::string> Symbol::ListOutputNames() const {
-  static auto& flist_ouputs = Op::GetAttr<FListOutputNames>("FListOutputNames");
+  static auto& flist_outputs = Op::GetAttr<FListOutputNames>("FListOutputNames");
 
   std::vector<std::string> ret;
   ret.reserve(outputs.size());
@@ -250,7 +250,7 @@ std::vector<std::string> Symbol::ListOutputNames() const {
     } else {
       const std::string& hname = head.node->attrs.name;
       std::string rname;
-      FListOutputNames fn = flist_ouputs.get(head.node->op(), nullptr);
+      FListOutputNames fn = flist_outputs.get(head.node->op(), nullptr);
       if (fn != nullptr) {
         rname = fn(head.node->attrs)[head.index];
       } else {

python/tvm/micro/contrib/zephyr.py

@@ -537,7 +537,7 @@ class QemuStartupFailureError(Exception):
 
 
 class QemuFdTransport(file_descriptor.FdTransport):
-    """An FdTransport subclass that escapes written data to accomodate the QEMU monitor.
+    """An FdTransport subclass that escapes written data to accommodate the QEMU monitor.
 
     It's supposedly possible to disable the monitor, but Zephyr controls most of the command-line
     arguments for QEMU and there are too many options which implictly enable the monitor, so this

python/tvm/relay/frontend/coreml.py

@@ -524,7 +524,7 @@ def coreml_op_to_relay(op, inname, outnames, etab):
             outname = outnames if isinstance(outnames, _base.string_types) else outnames[0]
             etab.set_expr(outname, outs, force_override=True)
         else:
-            # the number of ouputs from model op and tvm relay must be same
+            # the number of outputs from model op and tvm relay must be same
             assert len(outnames) == len(outs)
             for outname, out in zip(outnames, outs):
                 etab.set_expr(outname, out, force_override=True)

python/tvm/relay/testing/resnet.py

@@ -177,7 +177,7 @@ def resnet(
         Channel size of each stage
 
     num_classes : int
-        Ouput size of symbol
+        Output size of symbol
 
     data_shape : tuple of int.
         The shape of input data.

python/tvm/relay/testing/resnet_3d.py

@@ -174,7 +174,7 @@ def resnet(
         Channel size of each stage
 
     num_classes : int
-        Ouput size of symbol
+        Output size of symbol
 
     data_shape : tuple of int.
         The shape of input data.

python/tvm/relay/transform/transform.py

@@ -985,7 +985,7 @@ def transform(func, mod, ctx):
     """
 
     if opt_level is None:
-        raise ValueError("Please provide opt_level for the funtion pass.")
+        raise ValueError("Please provide opt_level for the function pass.")
 
     required = required if required else []
     if not isinstance(required, (list, tuple)):

python/tvm/tir/stmt.py

@@ -109,7 +109,7 @@ class For(Stmt):
         The loop variable.
 
     min_val : PrimExpr
-        The begining value.
+        The beginning value.
 
     extent : PrimExpr
         The length of the loop.

python/tvm/tir/transform/function_pass.py

@@ -130,7 +130,7 @@ def transform(func, mod, ctx):
     """
 
     if opt_level is None:
-        raise ValueError("Please provide opt_level for the funtion pass.")
+        raise ValueError("Please provide opt_level for the function pass.")
 
     required = required if required else []
     if not isinstance(required, (list, tuple)):

python/tvm/topi/arm_cpu/depthwise_conv2d.py

@@ -692,7 +692,7 @@ def _schedule_spatial_pack(cfg, s, data_vec, kernel_vec, conv, output, last):
     if kernel_vec.op.name == "kernel_vec":
         co, _, _, _, _ = s[kernel_vec].op.axis
         if autotvm.GLOBAL_SCOPE.in_tuning:
-            # kernel packing will be pre-computed during compliation, so we skip
+            # kernel packing will be pre-computed during compilation, so we skip
             # this part to make tuning records correct
             s[kernel_vec].pragma(co, "debug_skip_region")
         else:

python/tvm/topi/cuda/batch_matmul_tensorcore.py

@@ -291,7 +291,7 @@ def batch_matmul_tensorcore_cuda(x, y):
     x_shape = get_const_tuple(x.shape)
     y_shape = get_const_tuple(y.shape)
     assert x_shape[0] == y_shape[0], "batch dimension doesn't match"
-    assert x_shape[2] == y_shape[2], "shapes of x and y is inconsistant"
+    assert x_shape[2] == y_shape[2], "shapes of x and y is inconsistent"
     batch, M, K = x.shape
     N = y.shape[1]
     out_dtype = x.dtype

python/tvm/topi/cuda/rcnn/proposal.py

@@ -203,7 +203,7 @@ def argsort_ir(data_buf, out_index_buf):
 
 
 def nms_ir(sorted_bbox_buf, out_buf, nms_threshold):
-    """Non-maximum supression.
+    """Non-maximum suppression.
 
     Parameters
     ----------

python/tvm/topi/nn/batch_matmul.py

@@ -62,7 +62,7 @@ def batch_matmul(x, y, oshape=None, auto_scheduler_rewritten_layout=""):
     k = te.reduce_axis((0, K), name="k")
     if oshape is None:
         assert XB == YB or XB == 1 or YB == 1, "batch dimension doesn't match"
-        assert x_shape[2] == y_shape[2], "shapes of x and y is inconsistant"
+        assert x_shape[2] == y_shape[2], "shapes of x and y is inconsistent"
         batch = te.max(XB, YB)
         N = y.shape[1]
         oshape = (batch, M, N)

python/tvm/topi/random/kernel.py

@@ -121,7 +121,7 @@ def _threefry(
         Threefry will write to :code:`out_buf[out_offset:out_offset+4*product(out_shape)]`
 
     out_shape: number
-        Determines the number of ouput states to generate. :code:`state[i]` will correspond to
+        Determines the number of output states to generate. :code:`state[i]` will correspond to
         counter+i.
     """
     nrounds = 20

python/tvm/topi/testing/strided_slice_python.py

@@ -26,7 +26,7 @@ def strided_slice_python(data, begin, end, strides, slice_mode="end"):
         Input data
 
     begin : list
-        Begining of the slices.
+        Beginning of the slices.
 
     end : list
         End of the slices.
@@ -81,7 +81,7 @@ def strided_set_python(data, v, begin, end, strides):
         Value data
 
     begin : list
-        Begining of the slices.
+        Beginning of the slices.
 
     end : list
         End of the slices.

python/tvm/topi/utils.py

@@ -460,7 +460,7 @@ def make_idx(b, e, s, z, i):
 
     Returns
     -------
-    postion: Expr
+    position: Expr
         int expression that corresponds to an array position in the selection.
     """
     bc = tvm.tir.Select(s < 0, i <= e, i < b)

python/tvm/topi/vision/rcnn/proposal.py

@@ -231,7 +231,7 @@ def argsort_ir(data_buf, out_index_buf):
 
 
 def nms_ir(sorted_bbox_buf, out_buf, nms_threshold):
-    """Non-maximum supression.
+    """Non-maximum suppression.
 
     Parameters
     ----------

python/tvm/topi/x86/batch_matmul.py

@@ -49,7 +49,7 @@ def batch_matmul(cfg, x, y, out_shape=None):
     XB, M, XK = get_const_tuple(x.shape)
     YB, N, YK = get_const_tuple(y.shape)
     assert (XB == YB) or (YB == 1) or (XB == 1), "batch dimension doesn't match"
-    assert XK == YK, "shapes of x and y is inconsistant"
+    assert XK == YK, "shapes of x and y is inconsistent"
     B = te.max(XB, YB)
     K = XK
     if out_shape is not None:
@@ -151,7 +151,7 @@ def batch_matmul_blas_common(cfg, x, y, out_shape, lib):
         3-D with shape [batch, N, K]
     out_shape : tuple or None
         Shape of the output
-    lib : A contrib module which implements batch_matmul funtion
+    lib : A contrib module which implements batch_matmul function
         cblas and mkl are supported
 
     Returns
@@ -163,7 +163,7 @@ def batch_matmul_blas_common(cfg, x, y, out_shape, lib):
     XB, M, XK = get_const_tuple(x.shape)
     YB, N, YK = get_const_tuple(y.shape)
     assert XB == YB, "batch dimension doesn't match"
-    assert XK == YK, "shapes of x and y is inconsistant"
+    assert XK == YK, "shapes of x and y is inconsistent"
     if out_shape is not None:
         assert out_shape[0] == XB, "got invalid output shape"
         assert out_shape[1] == M, "got invalid output shape"

python/tvm/topi/x86/conv2d_avx_1x1.py

@@ -191,7 +191,7 @@ def _declaration_conv_nhwc_pack(cfg, Input, Filter, stride, padding, dilation, o
     pad_before = [0, pad_top, pad_left, 0]
     pad_after = [0, pad_down, pad_right, 0]
     PaddedInput = pad(Input, pad_before, pad_after, name="PaddedInput")
-    # todo: padding filter to accomodate the intrinsic
+    # todo: padding filter to accommodate the intrinsic
 
     # packing the Filter to let memory access be consecutive for AVX512 intrinsic
     # Done in pre-compute stage

src/relay/ir/dataflow_matcher.cc

@@ -734,7 +734,7 @@ class PatternGrouper {
           // Exit due to overlapping partitions
           return;
         } else if (kv.second != body) {
-          // if the node isn't the ouput of the group
+          // if the node isn't the output of the group
           auto node = matcher_->expr_graph_.node_map_.at(kv.first);
           for (auto* output : node->outputs_) {
             // and the node is used by nodes outside of the group

src/relay/ir/indexed_graph.cc

@@ -73,7 +73,7 @@ IndexedGraph<Expr> CreateIndexedGraph(const Expr& expr) {
       return std::move(graph_);
     }
 
-    /*! Default visitation pushes the parent to the child's ouputs and the child to the parent's
+    /*! Default visitation pushes the parent to the child's outputs and the child to the parent's
      * inputs*/
     void VisitExpr(const Expr& expr, NodePtr parent) override {
       auto current = graph_.node_map_[expr];
@@ -220,7 +220,7 @@ IndexedGraph<DFPattern> CreateIndexedGraph(const DFPattern& pattern) {
       return std::move(graph_);
     }
 
-    /*! Default visitation pushes the parent to the child's ouputs */
+    /*! Default visitation pushes the parent to the child's outputs */
     void VisitDFPattern(const DFPattern& pattern, NodePtr parent) override {
       auto current = graph_.node_map_[pattern];
       if (parent) {

src/relay/transforms/partition_graph.cc

@@ -177,7 +177,7 @@ class Partitioner : public MixedModeMutator {
       AnnotatedRegion region = GetRegion(GetRef<Call>(call));
 
       // TODO(@manupa-arm) : need to use the parent function (to which region
-      // belongs to) name/key for the funtions that are created
+      // belongs to) name/key for the functions that are created
       BaseFunc f = GetFunc(GetRef<Call>(call));
 
       // Traverse subgraph inputs.

src/runtime/c_runtime_api.cc

@@ -169,7 +169,7 @@ void DeviceAPI::SyncStreamFromTo(TVMContext ctx, TVMStreamHandle event_src,
 // {message1}
 // {message2}
 // {Stack trace:}    // stack traces follow by this line
-//   {trace 0}       // two spaces in the begining.
+//   {trace 0}       // two spaces in the beginning.
 //   {trace 1}
 //   {trace 2}
 //--------------------------------------------------------

src/tir/transforms/hoist_if_then_else.cc

@@ -168,7 +168,7 @@ class HoistCandidateSelector final : public StmtExprVisitor {
     // To stop hoisting if any of the block variables are used.
     //
     // In case we want to use hoisting in between certain passes
-    // which have interdependencies of the postioning of if nodes with scope var
+    // which have interdependencies of the positioning of if nodes with scope var
     // it is better to disable this section
     if (support_block_scope_hosting_) {
       if (IsRecordingOn()) {

tests/python/frontend/mxnet/model_zoo/resnet.py

@@ -182,7 +182,7 @@ def resnet(
     filter_list : list
         Channel size of each stage
     num_classes : int
-        Ouput size of symbol
+        Output size of symbol
     dataset : str
         Dataset type, only cifar10 and imagenet supports
     workspace : int

tests/python/frontend/onnx/test_forward.py

@@ -3502,7 +3502,7 @@ def verify_roi_align(
 # @tvm.testing.uses_gpu
 def test_non_max_suppression():
     def verify_nms(
-        boxes, scores, max_ouput_boxes_per_class, iou_threshold, score_threshold, output_dims
+        boxes, scores, max_output_boxes_per_class, iou_threshold, score_threshold, output_dims
     ):
         input_names = ["boxes", "scores", "max_output_boxes_per_class", "iou_threshold"]
         input_nodes = [