Handle np.transpose() and ndarray.T shortcut.

* Just the form without explicit permutation for now.

include/npcomp/Dialect/Numpy/NumpyOps.td

@@ -115,7 +115,7 @@ def Numpy_UfuncCallOp : Numpy_Op<"ufunc_call", []> {
 def Numpy_DotOp : Numpy_Op<"dot", []> {
   let summary = "Represents the `numpy.dot` operator";
   let description = [{
-    See: https://numpy.org/doc/stable/reference/generated/numpy.dot.html
+    See: https://docs.scipy.org/doc/numpy/reference/generated/numpy.dot.html
   }];
   let arguments = (ins
     Numpy_AnyArray:$a,
@@ -129,4 +129,25 @@ def Numpy_DotOp : Numpy_Op<"dot", []> {
   }];  
 }
 
+def Numpy_TransposeOp : Numpy_Op<"transpose", []> {
+  let summary = "Represents the `numpy.transpose` op with no permutation specified";
+  let description = [{
+    This op is equivalent to calling `numpy.transpose(arr)`, which reverses
+    the axes of the array. It is separate from the explicit form because it
+    is not always possible to locallly infer an appropriate axis transform
+    at the point of declaration.
+
+    See: https://docs.scipy.org/doc/numpy/reference/generated/numpy.transpose.html
+  }];
+  let arguments = (ins
+    Numpy_AnyArray:$a
+  );
+  let results = (outs
+    Numpy_AnyArray:$output
+  );
+  let assemblyFormat = [{
+    operands attr-dict `:` functional-type(operands, $output)
+  }];  
+}
+
 #endif // NPCOMP_DIALECT_NUMPY_NUMPY_OPS

python/npcomp/tracing/context.py

@@ -154,6 +154,13 @@ class TracedArray(np.lib.mixins.NDArrayOperatorsMixin):
     _assert_active(tc)    
     return tc._handle_array_func(func, types, args, kwargs)
 
+  @property
+  def T(self):
+    """Shortcut for transpose."""
+    tc = self._tc
+    _assert_active(tc)    
+    return tc._handle_array_func(np.transpose, [TracedArray], [self], {})
+    
 
 def _check_numpy_version():
   version = np.lib.NumpyVersion(np.__version__)

python/npcomp/tracing/emitters.py

@@ -259,9 +259,17 @@ class EmitterRegistry:
         self.register_ufunc(ufunc, "__call__",
                             GenericCallUfuncEmitter("numpy." + member))
     # Register generic 1-result array funcs.
-    for f, op_name in ((np.inner, "numpy.inner"), (np.outer, "numpy.outer"),
-                       (np.dot, "numpy.dot"), (np.vdot, "numpy.vdot"),
-                       (np.linalg.det, "numpy.linalg.det")):
+    GENERIC_FUNCS = (
+        (np.inner, "numpy.inner"),
+        (np.outer, "numpy.outer"),
+        (np.dot, "numpy.dot"),
+        (np.vdot, "numpy.vdot"),
+        (np.linalg.det, "numpy.linalg.det"),
+        # TODO: This needs a custom implementation to differentiate when
+        # axes is specified (this version will fail).
+        (np.transpose, "numpy.transpose"),
+    )
+    for f, op_name in GENERIC_FUNCS:
       self.register_array_func(f, GenericArrayFuncEmitter(op_name))
 
 

python/npcomp/tracing/mlir_trace.py

@@ -28,13 +28,14 @@ class ModuleBuilder:
     self.emitters = (emitter_registry
                      if emitter_registry else EmitterRegistry.create_default())
 
-  def trace(self, export_py_func: ExportPyFunction):
-    """Traces and exported python function."""
-    assert isinstance(export_py_func, ExportPyFunction), (
-        "Expected an exported python function (from the Exporter class)")
-    tracer = FunctionTracer(self, export_py_func)
-    with tracer:
-      tracer.trace()
+  def trace(self, *export_py_funcs: ExportPyFunction):
+    """Traces exported py functions."""
+    for export_py_func in export_py_funcs:
+      assert isinstance(export_py_func, ExportPyFunction), (
+          "Expected an exported python function (from the Exporter class)")
+      tracer = FunctionTracer(self, export_py_func)
+      with tracer:
+        tracer.trace()
 
 
 class FunctionTracer(TraceContext):

python/samples/transpose.py

@@ -0,0 +1,22 @@
+#  Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+#  See https://llvm.org/LICENSE.txt for license information.
+#  SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+import numpy as np
+import npcomp as npc
+from npcomp.types import *
+
+def transpose_attribute(a: np.ndarray) -> np.ndarray:
+  return a.T
+
+def transpose(a: np.ndarray) -> np.ndarray:
+  return np.transpose(a)
+
+# TODO: Implement subclassing and deriving constraints by run
+exp = npc.Exporter()
+exp.transpose_attribute = transpose_attribute
+exp.transpose = transpose
+
+mb = npc.tracing.ModuleBuilder()
+mb.trace(exp.transpose_attribute, exp.transpose)
+print(mb.module.to_asm())