[DOCS] Update API docs to reflect the status after the refactor. (#4907)

docs/_static/css/tvm_theme.css

@@ -38,3 +38,6 @@ nav .hidden-section {
     color: #404040 !important;
 }
 
+.wy-nav-content {
+    max-width: 950px !important;
+}

docs/api/python/dev.rst

-..  Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-
-..    http://www.apache.org/licenses/LICENSE-2.0
-
-..  Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
-
-Developer API
--------------
-This page contains modules that are used by developers of TVM.
-Many of these APIs are PackedFunc registered in C++ backend.
-
-
-
-tvm.expr
-~~~~~~~~
-.. automodule:: tvm.expr
-   :members:
-   :undoc-members:
-
-tvm.codegen
-~~~~~~~~~~~
-.. automodule:: tvm.codegen
-   :members:
-   :undoc-members:
-
-tvm.stmt
-~~~~~~~~
-.. automodule:: tvm.stmt
-   :members:
-   :undoc-members:
-
-tvm.ir_pass
-~~~~~~~~~~~
-.. autosummary::
-
-   tvm.ir_pass.Inline
-   tvm.ir_pass.Simplify
-   tvm.ir_pass.ConvertSSA
-   tvm.ir_pass.VerifySSA
-   tvm.ir_pass.CanonicalSimplify
-   tvm.ir_pass.StorageFlatten
-   tvm.ir_pass.VectorizeLoop
-   tvm.ir_pass.SkipVectorize
-   tvm.ir_pass.UnrollLoop
-   tvm.ir_pass.ThreadSync
-   tvm.ir_pass.StorageRewrite
-   tvm.ir_pass.MakeAPI
-   tvm.ir_pass.SplitHostDevice
-   tvm.ir_pass.InjectVirtualThread
-   tvm.ir_pass.LoopPartition
-   tvm.ir_pass.RemoveNoOp
-   tvm.ir_pass.SplitPipeline
-   tvm.ir_pass.LowerThreadAllreduce
-   tvm.ir_pass.LowerIntrin
-   tvm.ir_pass.LowerTVMBuiltin
-   tvm.ir_pass.NarrowChannelAccess
-
-.. automodule:: tvm.ir_pass
-   :members:
-
-tvm.ir_builder
-~~~~~~~~~~~~~~
-.. automodule:: tvm.ir_builder
-   :members:
-
-tvm.make
-~~~~~~~~
-.. automodule:: tvm.make
-   :members:

docs/api/python/build.rst → docs/api/python/driver.rst

@@ -15,10 +15,10 @@
     specific language governing permissions and limitations
     under the License.
 
-tvm.build
----------
+tvm.driver
+----------
+.. automodule:: tvm.driver
+
 .. autofunction:: tvm.lower
 
 .. autofunction:: tvm.build
-
-.. autofunction:: tvm.build_config

docs/api/python/error.rst

@@ -20,3 +20,4 @@ tvm.error
 .. automodule:: tvm.error
    :members:
    :imported-members:
+   :autosummary:

docs/api/python/hybrid.rst

@@ -18,11 +18,6 @@
 tvm.hybrid
 ----------
 .. automodule:: tvm.hybrid
-
-.. autosummary::
-
-   tvm.hybrid.parse
-   tvm.hybrid.script
-
-.. autofunction:: tvm.hybrid.parse
-.. autofunction:: tvm.hybrid.script
+   :members:
+   :imported-members:
+   :autosummary:

docs/api/python/index.rst

@@ -21,23 +21,19 @@ Python API
 .. toctree::
    :maxdepth: 2
 
-   tvm
    runtime
    ndarray
    error
    ir
    target
-   intrin
-   tensor
-   schedule
-   build
-   function
+   tir
+   te
+   driver
    autotvm
    rpc
    contrib
    graph_runtime
-   dev
-   topi
-   vta/index
    hybrid
    relay/index
+   vta/index
+   topi

docs/api/python/intrin.rst

-..  Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-
-..    http://www.apache.org/licenses/LICENSE-2.0
-
-..  Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
-
-tvm.intrin
-----------
-.. automodule:: tvm.intrin
-
-.. autosummary::
-
-   tvm.call_packed
-   tvm.call_pure_intrin
-   tvm.call_intrin
-   tvm.call_pure_extern
-   tvm.call_extern
-   tvm.call_llvm_intrin
-   tvm.register_intrin_rule
-   tvm.if_then_else
-   tvm.exp
-   tvm.log
-   tvm.floor
-   tvm.ceil
-   tvm.trunc
-   tvm.round
-   tvm.nearbyint
-   tvm.abs
-   tvm.isnan
-
-.. autofunction:: tvm.call_packed
-.. autofunction:: tvm.call_pure_intrin
-.. autofunction:: tvm.call_intrin
-.. autofunction:: tvm.call_pure_extern
-.. autofunction:: tvm.call_extern
-.. autofunction:: tvm.call_llvm_intrin
-.. autofunction:: tvm.register_intrin_rule
-.. autofunction:: tvm.if_then_else
-.. autofunction:: tvm.exp
-.. autofunction:: tvm.log
-.. autofunction:: tvm.floor
-.. autofunction:: tvm.ceil
-.. autofunction:: tvm.trunc
-.. autofunction:: tvm.round
-.. autofunction:: tvm.nearbyint
-.. autofunction:: tvm.abs
-.. autofunction:: tvm.isnan

docs/api/python/ir.rst

@@ -20,3 +20,4 @@ tvm.ir
 .. automodule:: tvm.ir
    :members:
    :imported-members:
+   :autosummary:

docs/api/python/ndarray.rst

@@ -23,14 +23,5 @@ tvm.runtime.ndarray
     :members:
     :inherited-members:
 
-
-.. autoclass:: tvm.runtime.TVMContext
-    :members:
-
-.. autofunction:: tvm.context
-.. autofunction:: tvm.cpu
-.. autofunction:: tvm.gpu
-.. autofunction:: tvm.opencl
-.. autofunction:: tvm.metal
 .. autofunction:: tvm.nd.array
 .. autofunction:: tvm.nd.empty

docs/api/python/relay/index.rst

@@ -15,7 +15,7 @@
     specific language governing permissions and limitations
     under the License.
 
-Relay API
+tvm.relay
 =========
 
 This document contains the Python API for the Relay frontend, optimizer, and
@@ -35,9 +35,7 @@ compiler stack.
    image
    analysis
    transform
-   module
    nn
    op
    scope_builder
-   ty
    vision

docs/api/python/relay/ty.rst

-..  Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-
-..    http://www.apache.org/licenses/LICENSE-2.0
-
-..  Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
-
-tvm.relay.ty
-------------
-
-.. automodule:: tvm.relay.ty
-    :members:
-
-.. autoclass:: tvm.relay.ty.Type
-    :members:
-
-.. autoclass:: tvm.relay.ty.TensorType
-    :members:
-
-.. autoclass:: tvm.relay.ty.Kind
-    :members:
-
-.. autoclass:: tvm.relay.ty.TypeVar
-    :members:
-
-.. autoclass:: tvm.relay.ty.TypeConstraint
-    :members:
-
-.. autoclass:: tvm.relay.ty.TupleType
-    :members:
-
-.. autoclass:: tvm.relay.ty.FuncType
-    :members:
-
-.. autoclass:: tvm.relay.ty.IncompleteType
-    :members:
-
-.. autoclass:: tvm.relay.ty.TypeRelation
-    :members:

docs/api/python/rpc.rst

@@ -18,22 +18,6 @@
 tvm.rpc
 -------
 .. automodule:: tvm.rpc
-
-.. autofunction:: tvm.rpc.connect
-.. autofunction:: tvm.rpc.connect_tracker
-
-.. autoclass:: tvm.rpc.TrackerSession
-    :members:
-    :inherited-members:
-
-.. autoclass:: tvm.rpc.RPCSession
-    :members:
-    :inherited-members:
-
-.. autoclass:: tvm.rpc.LocalSession
-    :members:
-    :inherited-members:
-
-.. autoclass:: tvm.rpc.Server
    :members:
-    :inherited-members:
+   :imported-members:
+   :autosummary:

docs/api/python/runtime.rst

@@ -19,6 +19,11 @@ tvm.runtime
 -----------
 
 .. automodule:: tvm.runtime
+   :members:
+   :imported-members:
+   :exclude-members: NDArray
+   :autosummary:
+
 
 .. autoclass:: tvm.runtime.PackedFunc
    :members:

docs/api/python/target.rst

@@ -20,3 +20,4 @@ tvm.target
 .. automodule:: tvm.target
     :members:
     :imported-members:
+    :autosummary:

docs/api/python/schedule.rst → docs/api/python/te.rst

@@ -15,22 +15,16 @@
     specific language governing permissions and limitations
     under the License.
 
-tvm.schedule
-------------
-.. automodule:: tvm.schedule
+tvm.te
+------
+.. Exclude the ops imported from tir.
 
-.. autoclass:: tvm.schedule.IterVar
+.. automodule:: tvm.te
    :members:
-
-.. autoclass:: tvm.schedule.Buffer
-    :members:
-
-.. autofunction:: tvm.create_schedule
-
-.. autoclass:: tvm.schedule.Schedule
-    :members:
-    :inherited-members:
-
-.. autoclass:: tvm.schedule.Stage
-    :members:
-    :inherited-members:
+   :imported-members:
+   :exclude-members:
+      exp, erf, tanh, sigmoid, log, cos, sin, atan, sqrt, rsqrt, floor, ceil,
+      trunc, abs, round, nearbyint, isnan, power, popcount, fmod, if_then_else,
+      div, indexdiv, indexmod, truncdiv, truncmod, floordiv, floormod,
+      comm_reducer, min, max, sum
+   :autosummary:

docs/api/python/relay/module.rst → docs/api/python/tir.rst

@@ -15,10 +15,10 @@
     specific language governing permissions and limitations
     under the License.
 
-tvm.relay.module
-----------------
-
-.. automodule:: tvm.relay.module
-
-.. autoclass:: tvm.relay.module.Module
+tvm.tir
+-------
+.. automodule:: tvm.tir
    :members:
+   :imported-members:
+   :exclude-members: PrimExpr
+   :autosummary:

docs/api/python/topi.rst

@@ -15,7 +15,7 @@
     specific language governing permissions and limitations
     under the License.
 
-TOPI
+topi
 ----
 .. automodule:: topi
 

docs/api/python/vta/index.rst

@@ -15,8 +15,8 @@
     specific language governing permissions and limitations
     under the License.
 
-VTA API
-=======
+vta
+===
 
 This document contains the python API to VTA compiler toolchain.
 

docs/conf.py

@@ -49,9 +49,9 @@ sys.path.insert(0, os.path.join(curr_path, '../vta/python'))
 
 # General information about the project.
 project = u'tvm'
-author = u'%s developers' % project
-copyright = u'2018, %s' % author
-github_doc_root = 'https://github.com/tqchen/tvm/tree/master/docs/'
+author = u'Apache Software Foundation'
+copyright = u'2019, %s' % author
+github_doc_root = 'https://github.com/apache/incubator-tvm/tree/master/docs/'
 
 # add markdown parser
 CommonMarkParser.github_doc_root = github_doc_root
@@ -73,6 +73,7 @@ extensions = [
     'sphinx.ext.napoleon',
     'sphinx.ext.mathjax',
     'sphinx_gallery.gen_gallery',
+    'autodocsumm'
 ]
 
 breathe_projects = {'tvm' : 'doxygen/xml/'}
@@ -139,9 +140,6 @@ pygments_style = 'sphinx'
 # If true, `todo` and `todoList` produce output, else they produce nothing.
 todo_include_todos = False
 
-# sort autodoc order by the source file.
-autodoc_member_order = 'bysource'
-
 # -- Options for HTML output ----------------------------------------------
 
 # The theme is set by the make target
@@ -199,9 +197,9 @@ def run_doxygen(folder):
 
 intersphinx_mapping = {
     'python': ('https://docs.python.org/{.major}'.format(sys.version_info), None),
-    'numpy': ('http://docs.scipy.org/doc/numpy/', None),
-    'scipy': ('http://docs.scipy.org/doc/scipy/reference', None),
-    'matplotlib': ('http://matplotlib.org/', None),
+    'numpy': ('https://docs.scipy.org/doc/numpy/', None),
+    'scipy': ('https://docs.scipy.org/doc/scipy/reference', None),
+    'matplotlib': ('https://matplotlib.org/', None),
 }
 
 from sphinx_gallery.sorting import ExplicitOrder
@@ -242,8 +240,8 @@ sphinx_gallery_conf = {
     'doc_module': ('tvm', 'numpy'),
 'reference_url': {
     'tvm': None,
-    'matplotlib': 'http://matplotlib.org',
-    'numpy': 'http://docs.scipy.org/doc/numpy-1.9.1'},
+    'matplotlib': 'https://matplotlib.org/',
+    'numpy': 'https://docs.scipy.org/doc/numpy/'},
     'examples_dirs': examples_dirs,
     'gallery_dirs': gallery_dirs,
     'subsection_order': subsection_order,
@@ -251,3 +249,7 @@ sphinx_gallery_conf = {
     'find_mayavi_figures': False,
     'expected_failing_examples': []
 }
+
+autodoc_default_options = {
+    'member-order': 'bysource',
+}

docs/contribute/committer_guide.rst

@@ -59,7 +59,7 @@ Here are some example applications of this principle:
 
 
 Shepherd a Pull Request
-----------------------
+-----------------------
 
 Here are some tips to shepherd a pull request.
 You can also take a look at the :ref:`code_review_guide`.

docs/contribute/error_handling.rst

@@ -15,25 +15,27 @@
     specific language governing permissions and limitations
     under the License.
 
-.. _error_guide:
+.. _error-handling-guide:
 
 Error Handling Guide
 ====================
 TVM contains structured error classes to indicate specific types of error.
 Please raise a specific error type when possible, so that users can
 write code to handle a specific error category if necessary.
-
-All the error types are defined in :any:`tvm.error` namespace.
 You can directly raise the specific error object in python.
 In other languages like c++, you simply add ``<ErrorType>:`` prefix to
 the error message(see below).
 
+.. note::
+
+   Please refer to :py:mod:`tvm.error` for the list of errors.
+
 Raise a Specific Error in C++
 -----------------------------
 You can add ``<ErrorType>:`` prefix to your error message to
 raise an error of the corresponding type.
 Note that you do not have to add a new type
-:any:`tvm.error.TVMError` will be raised by default when
+:py:class:`tvm.error.TVMError` will be raised by default when
 there is no error type prefix in the message.
 This mechanism works for both ``LOG(FATAL)`` and ``CHECK`` macros.
 The following code gives an example on how to do so.
@@ -55,7 +57,7 @@ Here is what will happen if we call the registered function:
 .. code::
 
   >>> import tvm
-  >>> tvm._api_internal._ErrorTest(0, 1)
+  >>> tvm.testing.ErrorTest(0, 1)
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
     File "/path/to/tvm/python/tvm/_ffi/_ctypes/function.py", line 190, in __call__
@@ -68,7 +70,7 @@ Here is what will happen if we call the registered function:
     File "/path/to/tvm/src/api/api_test.cc", line 80
   ValueError: Check failed: x == y (0 vs. 1) : expect x and y to be equal.
   >>>
-  >>> tvm._api_internal._ErrorTest(1, 1)
+  >>> tvm.testing.ErrorTest(1, 1)
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
     File "/path/to/tvm/python/tvm/_ffi/_ctypes/function.py", line 190, in __call__
@@ -95,7 +97,7 @@ We try to keep a reasonable amount of error types.
 If you feel there is a need to add a new error type, do the following steps:
 
 - Send a RFC proposal with a description and usage examples in the current codebase.
-- Add the new error type to :any:`tvm.error` with clear documents.
+- Add the new error type to :py:mod:`tvm.error` with clear documents.
 - Update the list in this file to include the new error type.
 - Change the code to use the new error type.
 
@@ -118,22 +120,3 @@ error messages when necessary.
 
 If we need to introduce a wrapper function that constructs multi-line error messages,
 please put wrapper in the same file so other developers can look up the implementation easily.
-
-
-System-wide Errors
-------------------
-
-.. autoclass:: tvm.error.TVMError
-
-.. autoclass:: tvm.error.InternalError
-
-
-Frontend Errors
----------------
-.. autoclass:: tvm.error.OpNotImplemented
-
-.. autoclass:: tvm.error.OpAttributeInvalid
-
-.. autoclass:: tvm.error.OpAttributeRequired
-
-.. autoclass:: tvm.error.OpAttributeNotImplemented

docs/dev/runtime.rst

@@ -183,7 +183,7 @@ RPC server on iPhone/android/raspberry pi or even the browser. The cross compila
 This instant feedback gives us a lot of advantages. For example, to test the correctness of generated code on iPhone, we no longer have to write test-cases in swift/objective-c from scratch -- We can use RPC to execute on iPhone, copy the result back and do verification on the host via numpy. We can also do the profiling using the same script.
 
 TVM Object and Compiler Stack
----------------------------
+-----------------------------
 
 As we mentioned earlier, we build compiler stack API on top of the PackedFunc runtime system.
 We faced a constant changing of the compiler API for the need of research. We need a new language object or IR node whenever we want to test out new primitives.

python/tvm/autotvm/tuner/xgboost_tuner.py

@@ -45,20 +45,24 @@ class XGBTuner(ModelBasedTuner):
         For cross-shape tuning (e.g. many convolutions with different shapes),
         'itervar' and 'curve' has better transferability,
         'knob' is faster.
+
         For cross-device or cross-operator tuning, you can use 'curve' only.
     loss_type: str
         If is 'reg', use regression loss to train cost model.
         The cost model predicts the normalized flops.
         If is 'rank', use pairwise rank loss to train cost model.
         The cost model predicts relative rank score.
+
     num_threads: int, optional
         The number of threads.  optimizer: str or ModelOptimizer, optional
         If is 'sa', use a default simulated annealing optimizer.
         Otherwise it should be a ModelOptimizer object.
+
     diversity_filter_ratio: int or float, optional
         If is not None, the tuner will first select
         top-(plan_size * diversity_filter_ratio) candidates according to the cost model
         and then pick batch_size of them according to the diversity metric.
+
     log_interval: int, optional
         The verbose level.
         If is 0, output nothing.

python/tvm/contrib/graph_runtime.py

@@ -25,19 +25,23 @@ from ..rpc import base as rpc_base
 
 def create(graph_json_str, libmod, ctx):
     """Create a runtime executor module given a graph and module.
+
     Parameters
     ----------
     graph_json_str : str or graph class
         The graph to be deployed in json format output by json graph.
         The graph can only contain one operator(tvm_op) that
         points to the name of PackedFunc in the libmod.
-    libmod : tvm.Module
+
+    libmod : tvm.runtime.Module
         The module of the corresponding function
+
     ctx : TVMContext or list of TVMContext
         The context to deploy the module. It can be local or remote when there
         is only one TVMContext. Otherwise, the first context in the list will
         be used as this purpose. All context should be given for heterogeneous
         execution.
+
     Returns
     -------
     graph_module : GraphModule
@@ -61,11 +65,14 @@ def create(graph_json_str, libmod, ctx):
 
 def get_device_ctx(libmod, ctx):
     """Parse and validate all the device context(s).
+
     Parameters
     ----------
-    libmod : tvm.Module
+    libmod : tvm.runtime.Module
         The module of the corresponding function
+
     ctx : TVMContext or list of TVMContext
+
     Returns
     -------
     ctx : list of TVMContext
@@ -113,12 +120,12 @@ class GraphModule(object):
 
     Parameters
     ----------
-    module : Module
+    module : tvm.runtime.Module
         The internal tvm module that holds the actual graph functions.
 
     Attributes
     ----------
-    module : Module
+    module : tvm.runtime.Module
         The internal tvm module that holds the actual graph functions.
     """
 

python/tvm/error.py

@@ -20,6 +20,10 @@ Each error class takes an error message as its input.
 See the example sections for for suggested message conventions.
 To make the code more readable, we recommended developers to
 copy the examples and raise errors with the same message convention.
+
+.. note::
+
+    Please also refer to :ref:`error-handling-guide`.
 """
 from tvm._ffi.base import register_error, TVMError
 

python/tvm/relay/op/nn/nn.py

@@ -1424,7 +1424,9 @@ def batch_norm(data,
 
     Besides the inputs and the outputs, this operator accepts two auxiliary
     states, ``moving_mean`` and ``moving_var``, which are *k*-length
-    vectors. They are global statistics for the whole dataset, which are updated by::
+    vectors. They are global statistics for the whole dataset, which are updated by
+
+    .. code:: python
 
         moving_mean = moving_mean * momentum + data_mean * (1 - momentum)
         moving_var = moving_var * momentum + data_var * (1 - momentum)

python/tvm/relay/op/tensor.py

@@ -847,6 +847,7 @@ def clip(a, a_min, a_max):
     Examples
     --------
     .. code:: python
+
       x = relay.Constant(tvm.nd.array([0, 1, 5, 3, 4, 2]))
       relay.clip(x, 1., 4.)
       # [1, 1, 4, 3, 4, 2]

python/tvm/target/__init__.py

@@ -51,7 +51,7 @@ The list of options include:
    It is useful in environments where dynamic loading api like dlopen is banned.
    The system lib will be available as long as the result code is linked by the program.
 
-We can use :py:func:`~tvm.target.create` to create a tvm.target.Target from the target string.
+We can use :py:func:`tvm.target.create` to create a tvm.target.Target from the target string.
 We can also use other specific function in this module to create specific targets.
 """
 from .target import Target, create

python/tvm/target/target.py

@@ -30,12 +30,12 @@ class Target(Object):
     ----
     Do not use class constructor, you can create target using the following functions
 
-    - :py:func:`~tvm.target.create` create target from string
-    - :py:func:`~tvm.target.arm_cpu` create arm_cpu target
-    - :py:func:`~tvm.target.cuda` create CUDA target
-    - :py:func:`~tvm.target.rocm` create ROCM target
-    - :py:func:`~tvm.target.mali` create Mali target
-    - :py:func:`~tvm.target.intel_graphics` create Intel Graphics target
+    - :py:func:`tvm.target.create` create target from string
+    - :py:func:`tvm.target.arm_cpu` create arm_cpu target
+    - :py:func:`tvm.target.cuda` create CUDA target
+    - :py:func:`tvm.target.rocm` create ROCM target
+    - :py:func:`tvm.target.mali` create Mali target
+    - :py:func:`tvm.target.intel_graphics` create Intel Graphics target
     """
     def __new__(cls):
         # Always override new to enable class
@@ -262,7 +262,7 @@ def create(target_str):
 
     Note
     ----
-    See the note on :py:mod:`~tvm.target` on target string format.
+    See the note on :py:mod:`tvm.target` on target string format.
     """
     if isinstance(target_str, Target):
         return target_str

python/tvm/te/__init__.py

@@ -15,12 +15,16 @@
 # specific language governing permissions and limitations
 # under the License.
 # pylint: disable=unused-import, redefined-builtin, wildcard-import
-"""Namespace for Tensor-level IR"""
+"""Namespace for Tensor Expression Language
+"""
 # expose all operators in tvm tir.op
-from tvm.tir.op import *
+from tvm.tir import exp, erf, tanh, sigmoid, log, cos, sin, atan, sqrt, rsqrt, floor, ceil
+from tvm.tir import trunc, abs, round, nearbyint, isnan, power, popcount, fmod, if_then_else
+from tvm.tir import div, indexdiv, indexmod, truncdiv, truncmod, floordiv, floormod
+from tvm.tir import comm_reducer, min, max, sum
 
 from .schedule import Schedule, create_schedule
-from .tensor import TensorSlice, Tensor
+from .tensor import Tensor
 from .tensor_intrin import decl_tensor_intrin
 from .tag import tag_scope
 from .operation import placeholder, compute, scan, extern, var, size_var