[Blocksparse] Pipeline for lowering dense model to sparse-dense (apac…

…he#5377)

python/setup.py

@@ -156,6 +156,7 @@ def get_package_data_files():
       zip_safe=False,
       install_requires=[
         'numpy',
+        'scipy',
         'decorator',
         'attrs',
         'psutil',

python/tvm/relay/__init__.py

@@ -53,6 +53,7 @@
 from . import frontend
 from . import backend
 from . import quantize
+from . import data_dep_optimization
 
 # Dialects
 from . import qnn

python/tvm/relay/analysis/__init__.py

@@ -28,3 +28,4 @@
 
 # Feature
 from . import feature
+from . import sparse_dense

python/tvm/relay/analysis/analysis.py

@@ -333,3 +333,21 @@ def extract_fused_functions(mod):
     for hash_, func in ret_mod.functions.items():
         ret[hash_] = func
     return ret
+
+
+def search_fc_transpose(expr):
+    """Search fc weight name in the patten: y = nn.dense(x, transpose(w, [1, 0]))
+
+    This function is used in the data_dep_optimization.simplify_fc_transpose method
+
+    Parameters
+    ----------
+    expr : tvm.relay.Expr
+
+    Returns
+    -------
+    ret : Array[String]
+        Array of weight variable name in pattern y = nn.dense(x, transpose(w, [1, 0]))
+    """
+    ret = _ffi_api.search_fc_transpose(expr)
+    return ret

python/tvm/relay/analysis/sparse_dense.py

@@ -0,0 +1,93 @@
+# 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.
+# pylint: disable=no-else-return
+# pylint: disable=unidiomatic-typecheck
+"""
+This file contains helper functions for convert dense model
+to block sparse model
+"""
+from collections import namedtuple
+import numpy as np
+import scipy.sparse as sp
+import tvm
+from . import _ffi_api
+
+
+SparseAnalysisResult = namedtuple("SparseAnalysisResult", [
+    "weight_name",
+    "weight_shape",
+])
+
+def _search_dense_op_weight(expr):
+    """Search name of weight in all ```nn.dense``` operator
+       This is a helpful function to determine which param need
+       to be converted to sparse
+
+    Parameters
+    ----------
+    expr : relay.Expr
+        Expr will be searched
+
+    Returns
+    -------
+    ret : Array[String]
+        name of weight in all ``nn.dense``` operator
+    """
+    return _ffi_api.search_dense_op_weight(expr)
+
+
+def process_params(expr, params, block_size, sparsity_threshold):
+    """[summary]
+
+    Parameters
+    ----------
+    expr : Relay.Expr
+        Expr of the network
+    params : Dict[String, tvm.nd.array]
+        parameters of the network
+    block_size : Tuple(int, int)
+        Blocksize in BSR matrix
+    sparsity_threshold : float
+        Minimal sparsity requirement for converting to sparse operation
+
+    Returns
+    -------
+    ret : Namedtuple[weight_name: Array[String], weight_shape: Array[Array[IntImm]]]
+        return names of qualified dense weight and the shape in BSR format
+    """
+    memo = SparseAnalysisResult(weight_name=[], weight_shape=[])
+    weight_names = _search_dense_op_weight(expr)
+    for name in weight_names:
+        name = str(name)
+        w_np = params[name].asnumpy()
+        sparsity = 1.0 - (np.count_nonzero(w_np) / w_np.size)
+        if sparsity >= sparsity_threshold:
+            sparse_weight = sp.bsr_matrix(w_np, blocksize=block_size)
+            # remove dense weight
+            del params[name]
+            memo.weight_name.append(name)
+            memo.weight_shape.append(list(sparse_weight.data.shape) +
+                                     list(sparse_weight.indices.shape) +
+                                     list(sparse_weight.indptr.shape))
+            params[name + ".data"] = tvm.nd.array(sparse_weight.data)
+            params[name + ".indices"] = tvm.nd.array(sparse_weight.indices)
+            params[name + ".indptr"] = tvm.nd.array(sparse_weight.indptr)
+    ret = SparseAnalysisResult(
+        weight_name=tvm.runtime.convert(memo.weight_name),
+        weight_shape=tvm.runtime.convert(memo.weight_shape)
+    )
+    return ret

python/tvm/relay/data_dep_optimization/__init__.py

@@ -0,0 +1,21 @@
+# 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.
+#pylint: disable=unused-argument, not-context-manager
+"""Optimizations involves changing of paramters"""
+
+from . import bsr_dense
+from . import simplify_fc_transpose

python/tvm/relay/data_dep_optimization/bsr_dense.py

@@ -0,0 +1,57 @@
+# 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.
+#pylint: disable=unused-argument, not-context-manager
+"""Automatic convert model from dense to block sparse"""
+
+from tvm import relay
+from tvm.relay.analysis.sparse_dense import process_params
+
+from .utils import _run_opt_pass
+
+def convert(func, params, blocksize, sparsity_threshold):
+    """Convert a dense func and according parameters to block sparse
+
+    Parameters
+    ----------
+    func : relay.Expr
+        Expr will be optimized to sparse operation
+    params : Dict[Srting, tvm.nd.array]
+        Parameters of the Expr
+    blocksize : Tuple(int, int)
+        Blocksize for BSR matrix
+    sparsity_threshold : float
+        Minimal sparsity requirement for converting.
+        If weight sparsity is lower than this threshold,
+        the dense operation will be kept.
+
+    Returns
+    -------
+    new_func: relay.Expr
+        Mutated Expr with sparse operations
+
+    params: Dict[Srting, tvm.nd.array]
+        New params with BSR matrix for mutated Expr
+    """
+    weight_info = process_params(func, params, blocksize, sparsity_threshold)
+    new_func = _run_opt_pass(
+        func,
+        relay.transform.DenseToSparse(
+            weight_info.weight_name,
+            weight_info.weight_shape
+        )
+    )
+    return new_func, params

python/tvm/relay/data_dep_optimization/simplify_fc_transpose.py

@@ -0,0 +1,60 @@
+# 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.
+#pylint: disable=unused-argument, not-context-manager
+"""Automatic optimize fc tranpose"""
+import numpy as np
+
+import tvm
+from tvm import relay
+from tvm.relay.analysis import search_fc_transpose
+
+from .utils import _run_opt_pass
+
+
+def convert(func, params):
+    """convert all ```y = nn.dense(x, transpose(w, [1, 0]))``` to
+        ```y = nn.dense(x, wt)```
+
+    Parameters
+    ----------
+    func : relay.Expr
+        Expr will be optimized
+    params : Dict[String, tvm.nd.array]
+        Parameters of Expr
+
+    Returns
+    -------
+    new_func : relay.Expr
+        Mutated Expr from ```y = nn.dense(x, transpose(w, [1, 0]))``` to
+        ```y = nn.dense(x, wt)```
+    params: Dict[String, tvm.nd.array]
+        Parameters of mutated Expr, with weights pre-transposed
+    """
+    weight_info = search_fc_transpose(func)
+    for item in weight_info:
+        name = str(item)
+        w_np = params[name].asnumpy()
+        new_w = np.transpose(w_np, axes=[1, 0])
+        params[name + ".T"] = tvm.nd.array(new_w)
+        del params[name]
+    new_func = _run_opt_pass(
+        func,
+        relay.transform.SimplifyFCTranspose(
+            weight_info,
+        )
+    )
+    return new_func, params

python/tvm/relay/data_dep_optimization/utils.py

@@ -0,0 +1,40 @@
+# 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.
+#pylint: disable=unused-argument, not-context-manager
+"""Utils functions for optimizations"""
+
+import tvm
+
+def _run_opt_pass(expr, opt_pass):
+    """Helper function to run pass
+
+    Parameters
+    ----------
+    expr : relay.Expr
+        Expr will be optimized
+    opt_pass : relay.Pass
+        Optimization pass
+
+    Returns
+    -------
+    ret: relay.Expr
+        Optimized Expr by running opt_pass
+    """
+    assert isinstance(opt_pass, tvm.transform.Pass)
+    mod = tvm.IRModule.from_expr(expr)
+    mod = opt_pass(mod)
+    return mod["main"]

python/tvm/relay/transform/transform.py

@@ -839,3 +839,43 @@ def visit_var(self, var):
                     return relay.Var(var.name_hint, relay.TensorType(new_shape, ty.dtype))
                 return var
         return ChangeBatchMutator().visit(func)
+
+
+def DenseToSparse(weight_name, weight_shape):
+    """
+    Rewrite qualified ```nn.dense operation``` to ```nn.sparse_dense```
+    This pass is used in ```data_dep_optimization.bsr_dense```
+    Parameters of this pass is generated by ```analysis.sparse_dense.process_params```
+
+    Parameters
+    ----------
+    weight_name: Array[String]
+      Names of weights which qualified sparse contrains
+
+    weight_shape: Array[Array[IntImm]]
+      Weights shape in BSR format.
+
+    Returns
+    -------
+    ret : tvm.transform.Pass
+        The registered DenseToSparse pass.
+    """
+    return _ffi_api.DenseToSparse(weight_name, weight_shape)
+
+def SimplifyFCTranspose(target_weight_name):
+    """
+    Rewrite ```y = nn.dense(x, transpose(w, [1, 0]))``` to ```y = nn.dense(x, wt)```
+    This pass is used in ```data_dep_optimization.simplify_fc_transpose```
+
+    Parameters
+    ----------
+    weight_name: Array[String]
+      Names of weights which qualified ```y = nn.dense(x, transpose(w, [1, 0]))```
+      This parameter is generated by ```analysis.search_fc_transpose``` function
+
+    Returns
+    -------
+    ret : tvm.transform.Pass
+        The registered SimplifyFCTranspose pass.
+    """
+    return _ffi_api.SimplifyFCTranspose(target_weight_name)