[incubator-tvm] branch master updated (44ff1f3 -> 2e93aef)
This is an automated email from the ASF dual-hosted git repository. tqchen pushed a change to branch master in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git. from 44ff1f3 [Relay] Handle ndarray_size in FoldConstant (#6156) add 2e93aef Improve error messages in graph tuner, graph runtime, and module loader. (#6148) No new revisions were added by this update. Summary of changes: python/tvm/autotvm/graph_tuner/base_graph_tuner.py | 3 +++ python/tvm/contrib/graph_runtime.py| 5 - src/runtime/library_module.cc | 19 +-- src/runtime/stackvm/stackvm_module.cc | 19 +-- 4 files changed, 41 insertions(+), 5 deletions(-)
[incubator-tvm] branch master updated: [Relay] Handle ndarray_size in FoldConstant (#6156)
This is an automated email from the ASF dual-hosted git repository.
marisa pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/master by this push:
new 44ff1f3 [Relay] Handle ndarray_size in FoldConstant (#6156)
44ff1f3 is described below
commit 44ff1f3b5ed0751fee39537a0e6e3870a74c930b
Author: lixiaoquan
AuthorDate: Wed Jul 29 06:49:21 2020 +0800
[Relay] Handle ndarray_size in FoldConstant (#6156)
* [Relay] Handle ndarray_size in FoldConstant
* Use Optional
---
src/relay/transforms/fold_constant.cc | 75 ---
tests/python/relay/test_pass_fold_constant.py | 22
2 files changed, 90 insertions(+), 7 deletions(-)
diff --git a/src/relay/transforms/fold_constant.cc
b/src/relay/transforms/fold_constant.cc
index 0b873bf..3f5ecaa 100644
--- a/src/relay/transforms/fold_constant.cc
+++ b/src/relay/transforms/fold_constant.cc
@@ -86,7 +86,8 @@ class ConstantFolder : public ExprMutator {
shape_func_op_(Op::Get("vm.shape_func")),
alloc_tensor_op_(Op::Get("memory.alloc_tensor")),
alloc_storage_op_(Op::Get("memory.alloc_storage")),
-cast_op_(Op::Get("cast")) {}
+cast_op_(Op::Get("cast")),
+ndarray_size_op_(Op::Get("ndarray_size")) {}
Expr VisitExpr_(const LetNode* op) final {
Expr value = this->Mutate(op->value);
@@ -128,6 +129,10 @@ class ConstantFolder : public ExprMutator {
return EvaluateShapeOf(res, origin_args, call->attrs);
}
+if (call->op == ndarray_size_op_) {
+ return EvaluateNdarraySize(res, origin_args, call->attrs);
+}
+
// We should think about potentially constant evaluation over these ops
too.
if (call->op == invoke_tvm_op_ || call->op == shape_func_op_ || call->op
== alloc_tensor_op_ ||
call->op == alloc_storage_op_) {
@@ -173,6 +178,7 @@ class ConstantFolder : public ExprMutator {
const Op& alloc_tensor_op_;
const Op& alloc_storage_op_;
const Op& cast_op_;
+ const Op& ndarray_size_op_;
// Convert value to expression.
Expr ObjectToExpr(const ObjectRef& value) {
@@ -223,10 +229,8 @@ class ConstantFolder : public ExprMutator {
CHECK(param != nullptr);
tvm::Array ishape;
-if (const ConstantNode* op = input.as()) {
- ishape = op->tensor_type()->shape;
-} else if (input->checked_type_.defined()) {
- ishape = input->checked_type().as()->shape;
+if (auto opt = GetConstantShape(input)) {
+ ishape = opt.value();
} else {
return expr;
}
@@ -261,12 +265,69 @@ class ConstantFolder : public ExprMutator {
shape = Constant(ndarray);
}
+return CastValue(shape, param->dtype);
+ }
+
+ // Evaluate a call to the ndarray_size operator for tensors with constant
+ // shapes.
+ Expr EvaluateNdarraySize(Expr expr, Array args, Attrs attrs) {
+Expr input = args[0];
+const auto* param = attrs.as();
+CHECK(param != nullptr);
+
+tvm::Array ishape;
+if (auto opt = GetConstantShape(input)) {
+ ishape = opt.value();
+} else {
+ return expr;
+}
+
+// Get the constant size
+DLContext ctx;
+ctx.device_type = kDLCPU;
+ctx.device_id = 0;
+runtime::NDArray value;
+DLDataType cdtype = DataType::Int(32);
+value = runtime::NDArray::Empty({1}, cdtype, ctx);
+int32_t* data = static_cast(value->data);
+if (ishape.size() == 0) {
+ *data = 0;
+} else {
+ *data = 1;
+ using ::tvm::tir::IntImmNode;
+ for (size_t i = 0; i < ishape.size(); ++i) {
+if (const IntImmNode* dim = ishape[i].as()) {
+ *data *= dim->value;
+} else {
+ return expr;
+}
+ }
+}
+
+Constant size = Downcast(ObjectToExpr(value));
+return CastValue(size, param->dtype);
+ }
+
+ Expr CastValue(const Expr& value, DataType dtype) {
// Cast the constant into correct dtype
auto cast_attrs = make_object();
-cast_attrs->dtype = param->dtype;
-Expr ret = Call(cast_op_, {shape}, Attrs(cast_attrs), {});
+cast_attrs->dtype = dtype;
+Expr ret = Call(cast_op_, {value}, Attrs(cast_attrs), {});
return ConstEvaluate(ret);
}
+
+ Optional> GetConstantShape(const Expr& input) {
+tvm::Array ishape;
+if (const ConstantNode* op = input.as()) {
+ ishape = op->tensor_type()->shape;
+} else if (input->checked_type_.defined()) {
+ ishape = input->checked_type().as()->shape;
+} else {
+ return Optional>(nullptr);
+}
+
+return Optional>(ishape);
+ }
};
Expr FoldConstant(const Expr& expr, const IRModule& mod) {
diff --git a/tests/python/relay/test_pass_fold_constant.py
b/tests/python/relay/test_pass_fold_constant.py
index fcccab5..e985268 100644
--- a/tests/python/relay/test_pass_fold_constant.py
+++ b/tests/python/relay/test_pass_fold_constant.py
@@ -164,6 +164,27 @@ def test_fold_shape_of():
assert
[incubator-tvm] branch master updated: [Topi, x86] Using MKL blas for quantized dense (#6115)
This is an automated email from the ASF dual-hosted git repository.
haichen pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/master by this push:
new 8cd53e0 [Topi, x86] Using MKL blas for quantized dense (#6115)
8cd53e0 is described below
commit 8cd53e00722d079290b53ade348b860f9c237ee9
Author: Animesh Jain
AuthorDate: Tue Jul 28 13:32:00 2020 -0700
[Topi, x86] Using MKL blas for quantized dense (#6115)
* [Topi, x86] Using MKL blas for quantized dense
* Typo
* CBLAS_OFFSET only available for MKL
* Skipping tests as GPU CI uses Openblas
* Retrigger
Co-authored-by: Ubuntu
---
python/tvm/contrib/cblas.py | 33 +
src/runtime/contrib/cblas/cblas.cc | 41 ++
src/runtime/contrib/cblas/gemm_common.h | 48 ++
tests/python/contrib/test_cblas.py | 52 +
topi/python/topi/x86/dense.py | 8 -
5 files changed, 181 insertions(+), 1 deletion(-)
diff --git a/python/tvm/contrib/cblas.py b/python/tvm/contrib/cblas.py
index e1a4a8a..68586dfd 100644
--- a/python/tvm/contrib/cblas.py
+++ b/python/tvm/contrib/cblas.py
@@ -52,6 +52,39 @@ def matmul(lhs, rhs, transa=False, transb=False, **kwargs):
)
+def matmul_u8s8s32(lhs, rhs, transa=False, transb=False, **kwargs):
+"""Create an extern op that compute matrix mult of A and rhs with CrhsLAS
+This function serves as an example on how to call external libraries.
+
+Parameters
+--
+lhs: Tensor
+The left matrix operand
+rhs: Tensor
+The right matrix operand
+transa: bool
+Whether transpose lhs
+transb: bool
+Whether transpose rhs
+
+Returns
+---
+C: Tensor
+The result tensor.
+"""
+n = lhs.shape[1] if transa else lhs.shape[0]
+m = rhs.shape[0] if transb else rhs.shape[1]
+return te.extern(
+(n, m),
+[lhs, rhs],
+lambda ins, outs: tvm.tir.call_packed(
+"tvm.contrib.cblas.matmul_u8s8s32", ins[0], ins[1], outs[0],
transa, transb
+),
+name="C",
+**kwargs
+)
+
+
def batch_matmul(lhs, rhs, transa=False, transb=False, iterative=False,
**kwargs):
"""Create an extern op that compute batched matrix mult of A and rhs with
CBLAS
This function serves as an example on how to call external libraries.
diff --git a/src/runtime/contrib/cblas/cblas.cc
b/src/runtime/contrib/cblas/cblas.cc
index 0cf4c69..e84ee11 100644
--- a/src/runtime/contrib/cblas/cblas.cc
+++ b/src/runtime/contrib/cblas/cblas.cc
@@ -44,8 +44,37 @@ using namespace runtime;
inline CBLAS_TRANSPOSE BooleanToTranspose(bool trans) { return trans ?
CblasTrans : CblasNoTrans; }
+#if USE_MKL_BLAS == 1
+inline CBLAS_OFFSET StringToOffset(const std::string offset_type) {
+ if (offset_type != "CblasFixOffset" && offset_type != "CblasColOffset" &&
+ offset_type != "CblasRowOffset") {
+LOG(FATAL) << "Unrecognized offset_type " << offset_type;
+ }
+ if (offset_type == "CblasFixOffset") {
+return CblasFixOffset;
+ } else if (offset_type == "CblasColOffset") {
+return CblasColOffset;
+ }
+ return CblasRowOffset;
+}
+#endif
+
inline char BooleanToTransposeChar(bool trans) { return trans ? 'T' : 'N'; }
+struct CblasGemmU8S8S32Op {
+ void operator()(bool ta, bool tb, int M, int N, int K, float alpha, const
void* A, int lda,
+ int offset_a, const void* B, int ldb, int offset_b, float
beta, int* C, int ldc,
+ const std::string offset_ctype, int* offset_c) {
+#if USE_MKL_BLAS == 1
+cblas_gemm_s8u8s32(CblasColMajor, BooleanToTranspose(ta),
BooleanToTranspose(tb),
+ StringToOffset(offset_ctype), M, N, K, alpha, A, lda,
offset_a, B, ldb,
+ offset_b, beta, C, ldc, offset_c);
+#else
+LOG(FATAL) << "Quantized Gemm is supported with MKL Blas only";
+#endif
+ }
+};
+
struct CblasSgemmOp {
typedef float TDatatype;
void operator()(bool ta, bool tb, int M, int N, int K, float alpha, float*
A, int lda, float* B,
@@ -170,6 +199,18 @@
TVM_REGISTER_GLOBAL("tvm.contrib.cblas.matmul").set_body([](TVMArgs args, TVMRet
CallGemm(args, ret, CblasDgemmOp());
});
+// integer matrix multiplication for row major
+TVM_REGISTER_GLOBAL("tvm.contrib.cblas.matmul_u8s8s32")
+.set_body([](TVMArgs args, TVMRetValue* ret) {
+ DLTensor* A = args[0];
+ DLTensor* B = args[1];
+ DLTensor* C = args[2];
+ CHECK(TypeMatch(A->dtype, kDLUInt, 8) && TypeMatch(B->dtype, kDLInt, 8)
&&
+TypeMatch(C->dtype, kDLInt, 32));
+
+ CallU8S8S32Gemm(args, ret, CblasGemmU8S8S32Op());
+});
+
TVM_REGISTER_GLOBAL("tvm.contrib.cblas.batch_matmul").set_body([](TVMArgs
args, TVMRetValue* ret) {
DLTensor* A = args[0];
[incubator-tvm] branch master updated: Correct runtime.load_module (#6161)
This is an automated email from the ASF dual-hosted git repository.
tqchen pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/master by this push:
new 1e9e4b9 Correct runtime.load_module (#6161)
1e9e4b9 is described below
commit 1e9e4b9fee46119c8bf52d8ea5d58301fe273780
Author: Tianqi Chen
AuthorDate: Tue Jul 28 13:18:14 2020 -0700
Correct runtime.load_module (#6161)
---
docs/deploy/hls.rst | 6 +++---
docs/dev/introduction_to_module_serialization.rst | 2 +-
docs/dev/relay_bring_your_own_codegen.rst | 6 +++---
rust/tvm/examples/resnet/src/build_resnet.py | 2 +-
4 files changed, 8 insertions(+), 8 deletions(-)
diff --git a/docs/deploy/hls.rst b/docs/deploy/hls.rst
index 64717ed..da1721d 100644
--- a/docs/deploy/hls.rst
+++ b/docs/deploy/hls.rst
@@ -64,11 +64,11 @@ We use two python scripts for this tutorial.
tgt="sdaccel"
- fadd = tvm.runtime.load("myadd.so")
+ fadd = tvm.runtime.load_module("myadd.so")
if os.environ.get("XCL_EMULATION_MODE"):
- fadd_dev = tvm.runtime.load("myadd.xclbin")
+ fadd_dev = tvm.runtime.load_module("myadd.xclbin")
else:
- fadd_dev = tvm.runtime.load("myadd.awsxclbin")
+ fadd_dev = tvm.runtime.load_module("myadd.awsxclbin")
fadd.import_module(fadd_dev)
ctx = tvm.context(tgt, 0)
diff --git a/docs/dev/introduction_to_module_serialization.rst
b/docs/dev/introduction_to_module_serialization.rst
index 78f6d71..5451b84 100644
--- a/docs/dev/introduction_to_module_serialization.rst
+++ b/docs/dev/introduction_to_module_serialization.rst
@@ -53,7 +53,7 @@ Let us build one ResNet-18 workload for GPU as an example
first.
resnet18_lib.export_library(path_lib)
# load it back
- loaded_lib = tvm.runtime.load(path_lib)
+ loaded_lib = tvm.runtime.load_module(path_lib)
assert loaded_lib.type_key == "library"
assert loaded_lib.imported_modules[0].type_key == "cuda"
diff --git a/docs/dev/relay_bring_your_own_codegen.rst
b/docs/dev/relay_bring_your_own_codegen.rst
index 0cced36..4d761bf 100644
--- a/docs/dev/relay_bring_your_own_codegen.rst
+++ b/docs/dev/relay_bring_your_own_codegen.rst
@@ -905,7 +905,7 @@ We also need to register this function to enable the
corresponding Python API:
TVM_REGISTER_GLOBAL("module.loadbinary_examplejson")
.set_body_typed(ExampleJsonModule::LoadFromBinary);
-The above registration means when users call ``tvm.runtime.load(lib_path)``
API and the exported library has an ExampleJSON stream, our ``LoadFromBinary``
will be invoked to create the same customized runtime module.
+The above registration means when users call
``tvm.runtime.load_module(lib_path)`` API and the exported library has an
ExampleJSON stream, our ``LoadFromBinary`` will be invoked to create the same
customized runtime module.
In addition, if you want to support module creation directly from an
ExampleJSON file, you can also implement a simple function and register a
Python API as follows:
@@ -930,7 +930,7 @@ In addition, if you want to support module creation
directly from an ExampleJSON
*rv = ExampleJsonModule::Create(args[0]);
});
-It means users can manually write/modify an ExampleJSON file, and use Python
API ``tvm.runtime.load("mysubgraph.examplejson", "examplejson")`` to construct
a customized module.
+It means users can manually write/modify an ExampleJSON file, and use Python
API ``tvm.runtime.load_module("mysubgraph.examplejson", "examplejson")`` to
construct a customized module.
***
Summary
@@ -954,7 +954,7 @@ In summary, here is a checklist for you to refer:
* ``Run`` to execute a subgraph.
* Register a runtime creation API.
* ``SaveToBinary`` and ``LoadFromBinary`` to serialize/deserialize
customized runtime module.
- * Register ``LoadFromBinary`` API to support
``tvm.runtime.load(your_module_lib_path)``.
+ * Register ``LoadFromBinary`` API to support
``tvm.runtime.load_module(your_module_lib_path)``.
* (optional) ``Create`` to support customized runtime module construction
from subgraph file in your representation.
* An annotator to annotate a user Relay program to make use of your compiler
and runtime (TBA).
diff --git a/rust/tvm/examples/resnet/src/build_resnet.py
b/rust/tvm/examples/resnet/src/build_resnet.py
index a09a0c3..1142f99 100644
--- a/rust/tvm/examples/resnet/src/build_resnet.py
+++ b/rust/tvm/examples/resnet/src/build_resnet.py
@@ -112,7 +112,7 @@ def download_img_labels():
def test_build(build_dir):
""" Sanity check with random input"""
graph = open(osp.join(build_dir, "deploy_graph.json")).read()
-lib = tvm.runtime.load(osp.join(build_dir, "deploy_lib.so"))
+lib = tvm.runtime.load_module(osp.join(build_dir, "deploy_lib.so"))
params = bytearray(open(osp.join(build_dir,"deploy_param.params"),
"rb").read())
[incubator-tvm] branch master updated (d35a149 -> a02d377)
This is an automated email from the ASF dual-hosted git repository. tqchen pushed a change to branch master in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git. from d35a149 [CI][Caffe Frontend] add caffe environment (#6023) add a02d377 [TIR][Bugfix] Improved massive build times caused by tir.floormod and tir.floordiv. Fixed Topi testcase. (#5666) No new revisions were added by this update. Summary of changes: src/target/llvm/codegen_llvm.cc | 8 +- src/target/llvm/codegen_llvm.h | 5 src/target/source/codegen_c.cc | 8 +- src/target/source/codegen_c.h| 5 src/target/spirv/codegen_spirv.cc| 8 +- src/target/spirv/codegen_spirv.h | 5 src/tir/transforms/lower_intrin.cc | 47 +--- src/tir/transforms/split_host_device.cc | 22 +-- topi/tests/python/test_topi_broadcast.py | 27 ++ 9 files changed, 96 insertions(+), 39 deletions(-)
[incubator-tvm] branch master updated (bbc2dbf -> d35a149)
This is an automated email from the ASF dual-hosted git repository.
tqchen pushed a change to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git.
from bbc2dbf [Ansor][AutoTVM v2.0] Phase 1: Add follow_split and
follow_fused_split steps (#6142)
add d35a149 [CI][Caffe Frontend] add caffe environment (#6023)
No new revisions were added by this update.
Summary of changes:
docker/Dockerfile.ci_cpu | 4
...buntu_install_nodejs.sh => ubuntu_install_caffe.sh} | 18 +++---
2 files changed, 15 insertions(+), 7 deletions(-)
copy docker/install/{ubuntu_install_nodejs.sh => ubuntu_install_caffe.sh} (66%)
mode change 100755 => 100644
[incubator-tvm] branch master updated: [Ansor][AutoTVM v2.0] Phase 1: Add follow_split and follow_fused_split steps (#6142)
This is an automated email from the ASF dual-hosted git repository.
lmzheng pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/master by this push:
new bbc2dbf [Ansor][AutoTVM v2.0] Phase 1: Add follow_split and
follow_fused_split steps (#6142)
bbc2dbf is described below
commit bbc2dbf9f81669c505ac8c73f4a6511bfc941d4f
Author: jiuqi-yang <68428961+jiuqi-y...@users.noreply.github.com>
AuthorDate: Tue Jul 28 22:49:05 2020 +0800
[Ansor][AutoTVM v2.0] Phase 1: Add follow_split and follow_fused_split
steps (#6142)
* Add cache_read/cache_write step
* Update
* Add follow split and follow fused split
Signed-off-by: jingbang.yjb
Conflicts:
src/auto_scheduler/compute_dag.cc
src/auto_scheduler/transform_step.cc
src/auto_scheduler/transform_step.h
tests/python/unittest/test_auto_scheduler_loop_state.py
* add loop_state.py
Signed-off-by: jingbang.yjb
* Update
* Update
* Update state->current_compute_dag to Optional
* Add some doc strings for Follow_Split and Follow_fused_split
Signed-off-by: jingbang.yjb
* Check code using c-lint
Signed-off-by: jingbang.yjb
* Add more doc strings and change the order for follow split.
Signed-off-by: jingbang.yjb
* Add record test for follow_split and follow_fused_split
Signed-off-by: jingbang.yjb
* Add record test for follow_split
Signed-off-by: jingbang.yjb
* Add record test for follow_fused_split.
Signed-off-by: jingbang.yjb
* Add test record for follow_fused_split
1. delete a comment
2. add "fuse" between follow_split and follow_fused_split
Signed-off-by: jingbang.yjb
* Add doc strings for some functions and variables
Signed-off-by: jingbang.yjb
* Fix the code format in src/auto_scheduler/transform_step.h
Signed-off-by: jingbang.yjb
* Update
* Update doc
* Update
* Update
* Fix follow_split and follow_fused_split record test.
Signed-off-by: jingbang.yjb
* Doc update
* Update some doc strings
Signed-off-by: jingbang.yjb
* Fix code style and some function definitions.
Signed-off-by: jingbang.yjb
* Update
Signed-off-by: jingbang.yjb
* Add comments on parameters.
Signed-off-by: jingbang.yjb
* Add more doc strings and fix some.
Signed-off-by: jingbang.yjb
* Update
Signed-off-by: jingbang.yjb
* Update
Signed-off-by: jingbang.yjb
* Update
Signed-off-by: jingbang.yjb
* Update.
Signed-off-by: jingbang.yjb
Co-authored-by: chengfan.jcf
Co-authored-by: jingbang.yjb
---
include/tvm/auto_scheduler/loop_state.h| 23 +++
include/tvm/auto_scheduler/transform_step.h| 168 -
python/tvm/auto_scheduler/loop_state.py| 96 ++
src/auto_scheduler/compute_dag.cc | 4 +-
src/auto_scheduler/loop_state.cc | 34
src/auto_scheduler/transform_step.cc | 208 -
.../unittest/test_auto_scheduler_loop_state.py | 42 -
.../python/unittest/test_auto_scheduler_measure.py | 25 ++-
8 files changed, 589 insertions(+), 11 deletions(-)
diff --git a/include/tvm/auto_scheduler/loop_state.h
b/include/tvm/auto_scheduler/loop_state.h
index 1c8ea77..9850620 100644
--- a/include/tvm/auto_scheduler/loop_state.h
+++ b/include/tvm/auto_scheduler/loop_state.h
@@ -359,6 +359,29 @@ class State : public ObjectRef {
TVM_DLL Array split(int stage_id, const Iterator& it,
const Array>& lengths,
bool inner_to_outer = true);
+ /*!
+ * \brief Schedule primitive extends to split step.
+ * \param stage_id The index of the stage to be split.
+ * \param it The iterator to be split.
+ * \param src_step_id The index of the split step to be followed in the
history.
+ * \param n_split The number of split level.
+ * \return The splitted new Iterators.
+ */
+ TVM_DLL Array follow_split(int stage_id, const Iterator& it, int
src_step_id,
+ int n_split);
+ /*!
+ * \brief Schedule primitive extends to split step.
+ * \param stage_id The index of the stage to be split.
+ * \param it The iterator to be split.
+ * \param src_step_ids The indices of the split steps to be followed in the
history.
+ * \param level Use the length in this split level.
+ * \param factor_or_nparts True to use `factor` for split from inner to
outer,
+ False to use `nparts` for split from outer to inner.
+ * \return The splitted new Iterators.
[incubator-tvm] branch master updated (ac1b0ea -> 6c17e65)
This is an automated email from the ASF dual-hosted git repository. tqchen pushed a change to branch master in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git. from ac1b0ea [DOCS][REFACTOR] Clarify Docs Categorization (#6155) add 6c17e65 Adding t-vi as a reviewer (#6149) No new revisions were added by this update. Summary of changes: CONTRIBUTORS.md | 1 + 1 file changed, 1 insertion(+)
[incubator-tvm] branch master updated: [DOCS][REFACTOR] Clarify Docs Categorization (#6155)
This is an automated email from the ASF dual-hosted git repository. tqchen pushed a commit to branch master in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git The following commit(s) were added to refs/heads/master by this push: new ac1b0ea [DOCS][REFACTOR] Clarify Docs Categorization (#6155) ac1b0ea is described below commit ac1b0ea18bf3c4b7258c6e81cc8ec9fecbb47131 Author: Tianqi Chen AuthorDate: Tue Jul 28 07:27:01 2020 -0700 [DOCS][REFACTOR] Clarify Docs Categorization (#6155) This PR categorizes the docs into a few categories: - How To - Tutorials - References - Deep Dive - MISC Co-authored-by: Chris Hoge Co-authored-by: Chris Hoge --- docs/index.rst | 14 -- 1 file changed, 4 insertions(+), 10 deletions(-) diff --git a/docs/index.rst b/docs/index.rst index defaf4a..18b2da7 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -37,11 +37,13 @@ For Developers .. toctree:: :maxdepth: 1 - :caption: Get Started + :caption: How to :hidden: install/index contribute/index + deploy/index + dev/how_to .. toctree:: :maxdepth: 1 @@ -52,13 +54,6 @@ For Developers .. toctree:: - :maxdepth: 1 - :caption: How-to Guide - :hidden: - - deploy/index - -.. toctree:: :maxdepth: 2 :caption: References :hidden: @@ -70,10 +65,9 @@ For Developers .. toctree:: :maxdepth: 2 :hidden: - :caption: For Developers + :caption: Deep Dive dev/index - dev/how_to .. toctree:: :maxdepth: 2
