Try to upgrade gast to 0.4.0

tensorflow/compiler/mlir/tfr/python/tfr_gen.py

@@ -1297,7 +1297,7 @@ def visit_Subscript(self, node):
     # TODO(fengliuai): Here we hardcode the node.slice here to get the index
     # type. Use the visit method once the type inference is done.
     # slice_val, slice_ty = self.visit(node.slice)
-    if isinstance(node.slice, ast.Index):
+    if isinstance(node.slice, ast.Slice):
       if isinstance(node.slice.value, ast.Constant):
         # TODO(fengliuai): promote to an assignment
         idx_val = self._ssa_name('cst')

tensorflow/python/autograph/converters/slices.py

@@ -36,7 +36,7 @@ class SliceTransformer(converter.Base):
   def _process_single_assignment(self, target, value):
     if not isinstance(target, gast.Subscript):
       return None
-    if not isinstance(target.slice, gast.Index):
+    if not isinstance(target.slice, gast.Slice):
       return None
 
     template = """
@@ -57,7 +57,7 @@ def visit_Assign(self, node):
 
   def visit_Subscript(self, node):
     node = self.generic_visit(node)
-    if not isinstance(node.slice, gast.Index):
+    if not isinstance(node.slice, gast.Slice):
       return node
 
     if not isinstance(node.ctx, gast.Load):

tensorflow/python/autograph/pyct/ast_util.py

@@ -274,7 +274,7 @@ def apply_to_single_assignments(targets, values, apply_fn):
           value_el = values.elts[i]
         else:
           idx = parser.parse_expression(str(i))
-          value_el = gast.Subscript(values, gast.Index(idx), ctx=gast.Load())
+          value_el = gast.Subscript(values, gast.Slice(idx,idx+1), ctx=gast.Load())
         apply_to_single_assignments(target_el, value_el, apply_fn)
     else:
       apply_fn(target, values)

tensorflow/python/autograph/pyct/qual_names.py

@@ -208,7 +208,7 @@ def ast(self):
     if self.has_subscript():
       return gast.Subscript(
           value=self.parent.ast(),
-          slice=gast.Index(self.qn[-1].ast()),
+          slice=gast.Slice(self.qn[-1].ast()),
           ctx=CallerMustSetThis)
     if self.has_attr():
       return gast.Attribute(
@@ -247,7 +247,7 @@ def visit_Subscript(self, node):
     # TODO(mdan): This may no longer apply if we overload getitem.
     node = self.generic_visit(node)
     s = node.slice
-    if not isinstance(s, gast.Index):
+    if not isinstance(s, gast.Slice):
       # TODO(mdan): Support range and multi-dimensional indices.
       # Continuing silently because some demos use these.
       return node

tensorflow/python/autograph/pyct/transformer.py

@@ -412,7 +412,7 @@ def apply_to_single_assignments(self, targets, values, apply_fn):
           if isinstance(values, (gast.Tuple, gast.List)):
             value_el = values.elts[i]
           else:
-            value_el = gast.Subscript(values, gast.Index(i), ctx=gast.Store())
+            value_el = gast.Subscript(values, gast.Slice(i,i+1), ctx=gast.Store())
           self.apply_to_single_assignments(target_el, value_el, apply_fn)
       else:
         # TODO(mdan): Look into allowing to rewrite the AST here.

tensorflow/python/eager/gradient_input_output_exclusions.py

@@ -131,7 +131,7 @@ def visit_Subscript(self, node):
       qn = anno.getanno(node, anno.Basic.QN)
       if isinstance(node.ctx, gast.Load):
         self.reads.add(qn)
-    elif not isinstance(node.slice, gast.Index):
+    elif not isinstance(node.slice, gast.Slice):
       if anno.hasanno(node, anno.Basic.QN):
         self.complex_reads.add(anno.getanno(node, anno.Basic.QN))
       elif anno.hasanno(node.value, anno.Basic.QN):

tensorflow/tools/ci_build/builds/pip_new.sh

@@ -469,7 +469,7 @@ install_tensorflow_pip() {
 
   # Install the gast package in the virtualenv. Installing it in user system
   # packages does not appear to port it over when creating a virtualenv.
-  ${PIP_BIN_PATH} install --upgrade "gast==0.3.3" || \
+  ${PIP_BIN_PATH} install --upgrade "gast==0.4.0" || \
     die "Error: gast install, upgrade FAILED"
 
 }

tensorflow/tools/ci_build/release/common.sh

@@ -137,7 +137,7 @@ function install_ubuntu_16_pip_deps {
   "${PIP_CMD}" install --user 'wheel ~= 0.35'
   "${PIP_CMD}" install --user 'wrapt ~= 1.12.1'
   # We need to pin gast dependency exactly
-  "${PIP_CMD}" install --user 'gast == 0.3.3'
+  "${PIP_CMD}" install --user 'gast == 0.4.0'
   # Finally, install tensorboard and estimator
   # Note that here we want the latest version that matches (b/156523241)
   "${PIP_CMD}" install --user --upgrade --force-reinstall 'tb-nightly ~= 2.4.0.a'
@@ -199,7 +199,7 @@ function install_macos_pip_deps {
   ${PIP_CMD} install $USER_FLAG 'wheel ~= 0.35'
   ${PIP_CMD} install $USER_FLAG 'wrapt ~= 1.12.1'
   # We need to pin gast dependency exactly
-  ${PIP_CMD} install $USER_FLAG 'gast == 0.3.3'
+  ${PIP_CMD} install $USER_FLAG 'gast == 0.4.0'
   # Finally, install tensorboard and estimator
   # Note that here we want the latest version that matches (b/156523241)
   ${PIP_CMD} install $USER_FLAG --upgrade --force-reinstall 'tb-nightly ~= 2.4.0.a'

tensorflow/tools/ci_build/release/common_win.bat

@@ -43,7 +43,7 @@ SET PATH=%PATH%;C:\%PYTHON_DIRECTORY%
 %PY_EXE% -m pip install "wheel ~= 0.35"
 %PY_EXE% -m pip install "wrapt ~= 1.12.1"
 @REM We need to pin gast dependency exactly
-%PY_EXE% -m pip install "gast == 0.3.3"
+%PY_EXE% -m pip install "gast == 0.4.0"
 @REM Finally, install tensorboard and estimator
 @REM Note that here we want the latest version that matches (b/156523241)
 %PY_EXE% -m pip install --upgrade --force-reinstall "tb-nightly ~= 2.4.0.a"

tensorflow/tools/pip_package/setup.py

@@ -91,7 +91,7 @@
     'wrapt ~= 1.12.1',
     # These packages need to be pinned exactly as newer versions are
     # incompatible with the rest of the ecosystem
-    'gast == 0.3.3',
+    'gast == 0.4.0',
     # TensorFlow ecosystem packages that TF exposes API for
     # These need to be in sync with the existing TF version
     # They are updated during the release process

tensorflow/workspace.bzl

@@ -450,12 +450,12 @@ def tf_repositories(path_prefix = "", tf_repo_name = ""):
     tf_http_archive(
         name = "gast_archive",
         build_file = clean_dep("//third_party:gast.BUILD"),
-        sha256 = "b881ef288a49aa81440d2c5eb8aeefd4c2bb8993d5f50edae7413a85bfdb3b57",
-        strip_prefix = "gast-0.3.3",
+        sha256 = "40feb7b8b8434785585ab224d1568b857edb18297e5a3047f1ba012bc83b42c1",
+        strip_prefix = "gast-0.4.0",
         system_build_file = clean_dep("//third_party/systemlibs:gast.BUILD"),
         urls = [
-            "http://mirror.tensorflow.org/files.pythonhosted.org/packages/12/59/eaa15ab9710a20e22225efd042cd2d6a0b559a0656d5baba9641a2a4a921/gast-0.3.3.tar.gz",
-            "https://files.pythonhosted.org/packages/12/59/eaa15ab9710a20e22225efd042cd2d6a0b559a0656d5baba9641a2a4a921/gast-0.3.3.tar.gz",
+            "http://mirror.tensorflow.org/files.pythonhosted.org/packages/83/4a/07c7e59cef23fb147454663c3271c21da68ba2ab141427c20548ae5a8a4d/gast-0.4.0.tar.gz",
+            "https://files.pythonhosted.org/packages/83/4a/07c7e59cef23fb147454663c3271c21da68ba2ab141427c20548ae5a8a4d/gast-0.4.0.tar.gz",
         ],
     )