add ffi wrapper for np.histogram

python/mxnet/_ffi/node_generic.py

@@ -52,6 +52,8 @@ def convert_to_node(value):
     """
     if isinstance(value, Integral):
         return _api_internal._Integer(value)
+    elif isinstance(value, float):
+        return _api_internal._Float(value)
     elif isinstance(value, (list, tuple)):
         value = [convert_to_node(x) for x in value]
         return _api_internal._ADT(*value)

python/mxnet/ndarray/numpy/_op.py

@@ -1734,13 +1734,13 @@ def histogram(a, bins=10, range=None, normed=None, weights=None, density=None):
     if isinstance(bins, numeric_types):
         if range is None:
             raise NotImplementedError("automatic range is not supported yet...")
-        return _npi.histogram(a, bin_cnt=bins, range=range)
+        return _api_internal.histogram(a, None, bins, range)
     if isinstance(bins, (list, tuple)):
         raise NotImplementedError("array_like bins is not supported yet...")
     if isinstance(bins, str):
         raise NotImplementedError("string bins is not supported yet...")
     if isinstance(bins, NDArray):
-        return _npi.histogram(a, bins=bins)
+        return _npi.histogram(a, bins, None, None)
     raise ValueError("np.histogram fails with", locals())
 
 

src/api/_api_internal/_api_internal.cc

@@ -43,6 +43,16 @@ MXNET_REGISTER_GLOBAL("_Integer")
     }
 });
 
+MXNET_REGISTER_GLOBAL("_Float")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+    using namespace runtime;
+    if (args[0].type_code() == kDLFloat) {
+      *ret = Integer(args[0].operator double());
+    } else {
+      LOG(FATAL) << "only accept float";
+    }
+});
+
 MXNET_REGISTER_GLOBAL("_ADT")
 .set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
     using namespace runtime;

src/api/operator/numpy/np_bincount_op.cc

@@ -6,9 +6,9 @@
  * 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

src/api/operator/numpy/np_cumsum.cc

@@ -6,9 +6,9 @@
  * 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

src/api/operator/numpy/np_histogram_op.cc

@@ -0,0 +1,81 @@
+/*
+ * 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.
+ */
+
+/*!
+ * \file np_histogram_op.cc
+ * \brief Implementation of the API of functions in src/operator/tensor/histogram.cc
+ */
+
+#include <mxnet/api_registry.h>
+#include <mxnet/runtime/packed_func.h>
+#include "../utils.h"
+#include "../../../operator/tensor/histogram-inl.h"
+
+namespace mxnet {
+
+MXNET_REGISTER_API("_npi.histogram")
+.set_body([](runtime::MXNetArgs args, runtime::MXNetRetValue* ret) {
+  using namespace runtime;
+  nnvm::NodeAttrs attrs;
+  const nnvm::Op* op = Op::Get("_npi_histogram");
+  op::HistogramParam param;
+  // parse bin_cnt
+  if (args[2].type_code() == kNull) {
+    param.bin_cnt = dmlc::nullopt;
+  } else {
+    param.bin_cnt = args[2].operator int();
+  }
+
+  // parse range
+  if (args[3].type_code() == kNull) {
+    param.range = dmlc::nullopt;
+  } else {
+    param.range = Tuple<double>(args[3].operator ObjectRef());
+  }
+
+  attrs.parsed = std::move(param);
+  attrs.op = op;
+  SetAttrDict<op::HistogramParam>(&attrs);
+
+  std::vector<NDArray*> inputs_vec;
+  int num_inputs = 0;
+
+  if (param.bin_cnt.has_value()) {
+    CHECK_EQ(args[1].type_code(), kNull)
+      << "bins should be None when bin_cnt is provided";
+    inputs_vec.push_back((args[0].operator NDArray*()));
+    num_inputs = 1;
+  } else {
+    CHECK_NE(args[1].type_code(), kNull)
+      << "bins should not be None when bin_cnt is not provided";
+    // inputs
+    inputs_vec.push_back((args[0].operator NDArray*()));
+    inputs_vec.push_back((args[1].operator NDArray*()));
+    num_inputs = 2;
+  }
+
+  // outputs
+  NDArray** out = nullptr;
+  int num_outputs = 0;
+  auto ndoutputs = Invoke(op, &attrs, num_inputs, inputs_vec.data(), &num_outputs, out);
+  *ret = ADT(0, {NDArrayHandle(ndoutputs[0]),
+                 NDArrayHandle(ndoutputs[1])});
+});
+
+}  // namespace mxnet

src/operator/tensor/histogram-inl.h

@@ -45,22 +45,30 @@ namespace mxnet {
 namespace op {
 
 struct HistogramParam : public dmlc::Parameter<HistogramParam> {
-    dmlc::optional<int> bin_cnt;
-    dmlc::optional<mxnet::Tuple<double>> range;
-    DMLC_DECLARE_PARAMETER(HistogramParam) {
-      DMLC_DECLARE_FIELD(bin_cnt)
-        .set_default(dmlc::optional<int>())
-        .describe("Number of bins for uniform case");
-      DMLC_DECLARE_FIELD(range)
-        .set_default(dmlc::optional<mxnet::Tuple<double>>())
-        .describe("The lower and upper range of the bins. if not provided, "
-                  "range is simply (a.min(), a.max()). values outside the "
-                  "range are ignored. the first element of the range must be "
-                  "less than or equal to the second. range affects the automatic "
-                  "bin computation as well. while bin width is computed to be "
-                  "optimal based on the actual data within range, the bin count "
-                  "will fill the entire range including portions containing no data.");
-    }
+  dmlc::optional<int> bin_cnt;
+  dmlc::optional<mxnet::Tuple<double>> range;
+  DMLC_DECLARE_PARAMETER(HistogramParam) {
+    DMLC_DECLARE_FIELD(bin_cnt)
+      .set_default(dmlc::optional<int>())
+      .describe("Number of bins for uniform case");
+    DMLC_DECLARE_FIELD(range)
+      .set_default(dmlc::optional<mxnet::Tuple<double>>())
+      .describe("The lower and upper range of the bins. if not provided, "
+                "range is simply (a.min(), a.max()). values outside the "
+                "range are ignored. the first element of the range must be "
+                "less than or equal to the second. range affects the automatic "
+                "bin computation as well. while bin width is computed to be "
+                "optimal based on the actual data within range, the bin count "
+                "will fill the entire range including portions containing no data.");
+  }
+
+  void SetAttrDict(std::unordered_map<std::string, std::string>* dict) {
+    std::ostringstream bin_cnt_s, range_s;
+    bin_cnt_s << bin_cnt;
+    range_s << range;
+    (*dict)["bin_cnt"] = bin_cnt_s.str();
+    (*dict)["range"] = range_s.str();
+  }
 };
 
 struct FillBinBoundsKernel {