From: Kim Date: Mon, 4 Nov 2019 16:04:02 +0000 (+0800) Subject: remove PEP498 f-string new feature for support python3.5 (#4250) X-Git-Tag: upstream/0.7.0~1695 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=996cf30e8d54b4bf58f0c9950475f47bba7e2c7e;p=platform%2Fupstream%2Ftvm.git remove PEP498 f-string new feature for support python3.5 (#4250) --- diff --git a/nnvm/tests/python/frontend/tensorflow/test_forward.py b/nnvm/tests/python/frontend/tensorflow/test_forward.py index ad581fb..b49d702 100644 --- a/nnvm/tests/python/frontend/tensorflow/test_forward.py +++ b/nnvm/tests/python/frontend/tensorflow/test_forward.py @@ -537,7 +537,7 @@ def _test_split(in_shape, axis, num_or_size_splits, dtype): num_split = len(num_or_size_splits) if isinstance(num_or_size_splits, list) else num_or_size_splits tf.split(in_data, num_or_size_splits, axis=axis) - compare_tf_with_tvm([np_data], ['in_data:0'], [f'split:{n}' for n in range(num_split)]) + compare_tf_with_tvm([np_data], ['in_data:0'], ['split:{0}'.format(n) for n in range(num_split)]) # and now test together with concat tf.reset_default_graph() @@ -586,7 +586,7 @@ def _test_unstack(ip_shape, axis, dtype): in_data = tf.placeholder(dtype, ip_shape, name="in_data") tf.unstack(in_data, axis=axis) - compare_tf_with_tvm([np_data], ['in_data:0'], [f'unstack:{n}' for n in range(ip_shape[axis])]) + compare_tf_with_tvm([np_data], ['in_data:0'], ['unstack:{0}'.format(n) for n in range(ip_shape[axis])]) tf.reset_default_graph() in_data = tf.placeholder(dtype, ip_shape, name="in_data") diff --git a/python/tvm/relay/_parser.py b/python/tvm/relay/_parser.py index 3251088..eba92bf 100644 --- a/python/tvm/relay/_parser.py +++ b/python/tvm/relay/_parser.py @@ -215,7 +215,7 @@ class ParseTreeToRelayIR(RelayVisitor): def mk_global_var(self, name: str) -> expr.GlobalVar: """Create a new GlobalVar and add it to the GlobalVar scope.""" if name in self.global_vars: - raise ParseError(f"duplicate global var \"{name}\"") + raise ParseError("duplicate global var \"{0}\"".format(name)) var = expr.GlobalVar(name) self.global_vars[name] = var return var @@ -252,14 +252,15 @@ class ParseTreeToRelayIR(RelayVisitor): new_typ_name = self._type_expr_name(new_expr) existing_typ_name = self._type_expr_name(self.global_type_vars[name]) raise ParseError( - f"{new_typ_name} `{name}` conflicts with existing {existing_typ_name}") + "{0} `{1}` conflicts with existing {2}".format(new_typ_name,\ + name, existing_typ_name)) def _type_expr_name(self, e): if isinstance(e, adt.Constructor): - return f"`{e.belong_to.var.name}` ADT constructor" + return "`{0}` ADT constructor".format(e.belong_to.var.name) elif isinstance(e, ty.GlobalTypeVar): if e.kind == ty.Kind.AdtHandle: - return f"ADT definition" + return "ADT definition" return "function definition" def visitProjection(self, ctx): @@ -282,7 +283,7 @@ class ParseTreeToRelayIR(RelayVisitor): raise ParseError("unrecognized BOOL_LIT: `{}`".format(node_text)) if node_type == RelayLexer.QUOTED_STRING: return literal_eval(node_text) - raise ParseError(f"unhandled terminal \"{node_text}\" of type `{node_type}`") + raise ParseError("unhandled terminal \"{0}\" of type `{1}`".format(node_text, node_type)) def visitGeneralIdent(self, ctx): name = ctx.getText() @@ -310,14 +311,14 @@ class ParseTreeToRelayIR(RelayVisitor): var_name = ctx.CNAME().getText() global_var = self.global_vars.get(var_name, None) if global_var is None: - raise ParseError(f"unbound global var `{var_name}`") + raise ParseError("unbound global var `{0}`".format(var_name)) return global_var def visitLocalVar(self, ctx): var_name = ctx.CNAME().getText() local_var = lookup(self.var_scopes, var_name) if local_var is None: - raise ParseError(f"unbound local var `{var_name}`") + raise ParseError("unbound local var `{0}`".format(var_name)) return local_var def visitGraphVar(self, ctx): @@ -557,7 +558,7 @@ class ParseTreeToRelayIR(RelayVisitor): elif match_type == "match?": complete_match = False else: - raise RuntimeError(f"unknown match type {match_type}") + raise RuntimeError("unknown match type {0}".format(match_type)) match_data = self.visit(ctx.expr()) match_clauses = ctx.matchClauseList() diff --git a/python/tvm/relay/memory_alloc.py b/python/tvm/relay/memory_alloc.py index 7116af3..77f634f 100644 --- a/python/tvm/relay/memory_alloc.py +++ b/python/tvm/relay/memory_alloc.py @@ -50,7 +50,7 @@ class LinearizeRetType: for field_ty in typ.fields: _unpack(field_ty, out) else: - raise Exception(f"unsupported Relay type: {typ}") + raise Exception("unsupported Relay type: {0}".format(typ)) output = [] _unpack(self.typ, output) @@ -67,7 +67,7 @@ class LinearizeRetType: _pack(value[i], field_ty, tuple_out) out.append(expr.Tuple(tuple_out)) else: - raise Exception(f"unsupported Relay type: {typ}") + raise Exception("unsupported Relay type: {0}".format(typ)) if len(seq) == 1: return seq[0] @@ -144,11 +144,11 @@ class ManifestAllocPass(ExprMutator): size = self.compute_storage(tensor_type) alignment = self.compute_alignment(tensor_type.dtype) dtype = tensor_type.dtype - sto = scope.let(f"storage_{i}", self.alloc_storage( + sto = scope.let("storage_{0}".format(i), self.alloc_storage( size, alignment, dtype)) # TODO(@jroesch): There is a bug with typing based on the constant shape. tensor = self.alloc_tensor(sto, shape, dtype, tensor_type.shape) - return scope.let(f"tensor_{i}", tensor) + return scope.let("tensor_{0}".format(i), tensor) def visit_let(self, let): scope = ScopeBuilder() @@ -192,13 +192,13 @@ class ManifestAllocPass(ExprMutator): if state == 2: sh_of = self.visit(self.shape_of(arg)) shape_func_ins.append( - scope.let(f"in_shape_{i}", sh_of)) + scope.let("in_shape_{0}".format(i), sh_of)) is_inputs.append(0) # Pass Inputs elif state == 1: new_arg = self.visit(arg) shape_func_ins.append( - scope.let(f"in_shape_{i}", new_arg)) + scope.let("in_shape_{0}".format(i), new_arg)) is_inputs.append(1) # TODO(@jroesch): handle 3rd case else: @@ -208,7 +208,7 @@ class ManifestAllocPass(ExprMutator): for i, out in enumerate(cfunc.outputs): tt = ty.TensorType(out.shape, out.dtype) alloc = self.make_static_allocation(scope, tt, i) - alloc = scope.let(f"shape_func_out_{i}", alloc) + alloc = scope.let("shape_func_out_{0}".format(i), alloc) out_shapes.append(alloc) shape_call = self.shape_func( @@ -226,7 +226,7 @@ class ManifestAllocPass(ExprMutator): size = self.compute_storage_in_relay( out_shape, out_type.dtype) alignment = self.compute_alignment(out_type.dtype) - sto = scope.let(f"storage_{i}", self.alloc_storage( + sto = scope.let("storage_{i}".format(i=i), self.alloc_storage( size, alignment, out_type.dtype)) storages.append(sto) @@ -238,7 +238,7 @@ class ManifestAllocPass(ExprMutator): out_shape, out_type.dtype, out_type.shape) - alloc = scope.let(f"out_{i}", alloc) + alloc = scope.let("out_{i}".format(i=i), alloc) outs.append(alloc) invoke = self.invoke_tvm(call.op, ins, expr.Tuple(outs)) diff --git a/rust/frontend/README.md b/rust/frontend/README.md index 31d4806..4e11dd9 100644 --- a/rust/frontend/README.md +++ b/rust/frontend/README.md @@ -128,7 +128,7 @@ from tvm.contrib import cc def test_add(target_dir): if not tvm.module.enabled("cuda"): - print(f"skip {__file__} because cuda is not enabled...") + print("skip {__file__} because cuda is not enabled...".format(__file__=__file__)) return n = tvm.var("n") A = tvm.placeholder((n,), name='A')