histogram python dev

mindspore/ccsrc/utils/summary.proto

@@ -61,6 +61,30 @@ message Summary {
         required bytes encoded_image = 4;
     }
 
+    message Histogram {
+      message bucket{
+          // Count number of values fallen in [left, left + width).
+          // For the right most bucket, range is [left, left + width].
+          required double left = 1;
+          required double width = 2;
+          required int64 count = 3;
+      }
+  
+      repeated bucket buckets = 1;
+      optional int64 nan_count = 2;
+      optional int64 pos_inf_count = 3;
+      optional int64 neg_inf_count = 4;
+
+      // max, min, sum will not take nan and inf into account.
+      // If there is no valid value in tensor, max will be nan, min will be nan, sum will be 0.
+      optional double max = 5;
+      optional double min = 6;
+      optional double sum = 7;
+
+      // total number of values, including nan and inf
+      optional int64 count = 8;
+    }
+
     message Value {
         // Tag name for the data.
         required string tag = 1;
@@ -70,6 +94,7 @@ message Summary {
             float scalar_value = 3;
             Image image = 4;
             TensorProto tensor = 8;
+            Histogram histogram = 9;
         }
     }
 

mindspore/train/summary/_summary_adapter.py

@@ -71,12 +71,14 @@ class SummaryType(Enum):
         TENSOR (Number): Summary TENSOR enum.
         IMAGE (Number): Summary image enum.
         GRAPH (Number): Summary graph enum.
+        HISTOGRAM (Number): Summary histogram enum.
         INVALID (Number): Unknow type.
     """
     SCALAR = 1      # Scalar summary
     TENSOR = 2      # Tensor summary
     IMAGE = 3       # Image summary
     GRAPH = 4       # graph
+    HISTOGRAM = 5   # Histogram Summary
     INVALID = 0xFF  # unknow type
 
 
@@ -148,7 +150,7 @@ def package_summary_event(data_id, step):
     """
     data_list = get_summary_data(data_id)
     if data_list is None:
-        logger.error("The step(%r) does not have record data.", self.step)
+        logger.error("The step(%r) does not have record data.", step)
     del_summary_data(data_id)
     # create the event of summary
     summary_event = Event()
@@ -177,6 +179,12 @@ def package_summary_event(data_id, step):
             summary_value.tag = tag
             summary_image = summary_value.image
             _get_image_summary(tag, data, summary_image, MS_IMAGE_TENSOR_FORMAT)
+        elif summary_type is SummaryType.HISTOGRAM:
+            logger.debug("Now process Histogram summary, tag = %r", tag)
+            summary_value = summary.value.add()
+            summary_value.tag = tag
+            summary_histogram = summary_value.histogram
+            _fill_histogram_summary(tag, data, summary_histogram)
         else:
             # The data is invalid ,jump the data
             logger.error("Summary type is error, tag = %r", tag)
@@ -284,6 +292,74 @@ def _get_tensor_summary(tag: str, np_value, summary_tensor):
     return summary_tensor
 
 
+def _fill_histogram_summary(tag: str, np_value: np.array, summary_histogram) -> None:
+    """
+    Package the histogram summary.
+
+    Args:
+        tag (str): Summary tag describe.
+        np_value (np.array): Summary data.
+        summary_histogram (summary_pb2.Summary.Histogram): Summary histogram data.
+    """
+    logger.debug("Set(%r) the histogram summary value", tag)
+    # Default bucket for tensor with no valid data.
+    default_bucket_left = -0.5
+    default_bucket_width = 1.0
+
+    if np_value.size == 0:
+        bucket = summary_histogram.buckets.add()
+        bucket.left = default_bucket_left
+        bucket.width = default_bucket_width
+        bucket.count = 0
+
+        summary_histogram.nan_count = 0
+        summary_histogram.pos_inf_count = 0
+        summary_histogram.neg_inf_count = 0
+
+        summary_histogram.max = 0
+        summary_histogram.min = 0
+        summary_histogram.sum = 0
+
+        summary_histogram.count = 0
+
+        return
+
+    summary_histogram.nan_count = np.count_nonzero(np.isnan(np_value))
+    summary_histogram.pos_inf_count = np.count_nonzero(np.isposinf(np_value))
+    summary_histogram.neg_inf_count = np.count_nonzero(np.isneginf(np_value))
+    summary_histogram.count = np_value.size
+
+    masked_value = np.ma.masked_invalid(np_value)
+    tensor_max = masked_value.max()
+    tensor_min = masked_value.min()
+    tensor_sum = masked_value.sum()
+
+    # No valid value in tensor.
+    if tensor_max is np.ma.masked:
+        bucket = summary_histogram.buckets.add()
+        bucket.left = default_bucket_left
+        bucket.width = default_bucket_width
+        bucket.count = 0
+
+        summary_histogram.max = np.nan
+        summary_histogram.min = np.nan
+        summary_histogram.sum = 0
+
+        return
+
+    counts, edges = np.histogram(np_value, bins='auto', range=(tensor_min, tensor_max))
+
+    for ind, count in enumerate(counts):
+        bucket = summary_histogram.buckets.add()
+        bucket.left = edges[ind]
+        bucket.width = edges[ind + 1] - edges[ind]
+        bucket.count = count
+
+    summary_histogram.max = tensor_max
+    summary_histogram.min = tensor_min
+    summary_histogram.sum = tensor_sum
+
+
 def _get_image_summary(tag: str, np_value, summary_image, input_format='NCHW'):
     """
     Package the image summary.

mindspore/train/summary/_summary_scheduler.py

@@ -23,6 +23,7 @@ from ._summary_adapter import SummaryType, package_summary_event, save_summary_d
 FORMAT_SCALAR_STR = "Scalar"
 FORMAT_TENSOR_STR = "Tensor"
 FORMAT_IMAGE_STR = "Image"
+FORMAT_HISTOGRAM_STR = "Histogram"
 FORMAT_BEGIN_SLICE = "[:"
 FORMAT_END_SLICE = "]"
 
@@ -95,6 +96,8 @@ def _parse_tag_format(tag: str):
         summary_type = SummaryType.TENSOR
     elif type_str == FORMAT_IMAGE_STR:
         summary_type = SummaryType.IMAGE
+    elif type_str == FORMAT_HISTOGRAM_STR:
+        summary_type = SummaryType.HISTOGRAM
     else:
         logger.error("The tag(%s) type is invalid.", tag)
         summary_type = SummaryType.INVALID

tests/ut/python/train/summary/summary_reader.py

@@ -0,0 +1,43 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed 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.
+# ============================================================================
+"""Summary reader."""
+import struct
+
+import mindspore.train.summary_pb2 as summary_pb2
+
+_HEADER_SIZE = 8
+_HEADER_CRC_SIZE = 4
+_DATA_CRC_SIZE = 4
+
+
+class SummaryReader:
+    """Read events from summary file."""
+
+    def __init__(self, file_name):
+        self._file_name = file_name
+        self._file_handler = open(self._file_name, "rb")
+        # skip version event
+        self.read_event()
+
+    def read_event(self):
+        """Read next event."""
+        file_handler = self._file_handler
+        header = file_handler.read(_HEADER_SIZE)
+        data_len = struct.unpack('Q', header)[0]
+        file_handler.read(_HEADER_CRC_SIZE)
+        event_str = file_handler.read(data_len)
+        file_handler.read(_DATA_CRC_SIZE)
+        summary_event = summary_pb2.Event.FromString(event_str)
+        return summary_event

tests/ut/python/train/summary/test_histogram_summary.py

@@ -0,0 +1,210 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed 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.
+# ============================================================================
+"""Test histogram summary."""
+
+import logging
+import os
+import tempfile
+
+import numpy as np
+
+from mindspore.common.tensor import Tensor
+from mindspore.train.summary.summary_record import SummaryRecord, _cache_summary_tensor_data
+from .summary_reader import SummaryReader
+
+CUR_DIR = os.getcwd()
+SUMMARY_DIR = os.path.join(CUR_DIR, "/test_temp_summary_event_file/")
+
+LOG = logging.getLogger("test")
+LOG.setLevel(level=logging.ERROR)
+
+
+def _wrap_test_data(input_data: Tensor):
+    """
+    Wraps test data to summary format.
+
+    Args:
+        input_data (Tensor): Input data.
+
+    Returns:
+        dict, the wrapped data.
+    """
+
+    return [{
+        "name": "test_data[:Histogram]",
+        "data": input_data
+    }]
+
+
+def test_histogram_summary():
+    """Test histogram summary."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
+
+        test_data = _wrap_test_data(Tensor([[1, 2, 3], [4, 5, 6]]))
+        _cache_summary_tensor_data(test_data)
+        test_writer.record(step=1)
+        test_writer.close()
+
+        file_name = os.path.join(tmp_dir, test_writer.event_file_name)
+        reader = SummaryReader(file_name)
+        event = reader.read_event()
+        assert event.summary.value[0].histogram.count == 6
+
+
+def test_histogram_multi_summary():
+    """Test histogram multiple step."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
+
+        rng = np.random.RandomState(10)
+        size = 50
+        num_step = 5
+
+        for i in range(num_step):
+            arr = rng.normal(size=size)
+
+            test_data = _wrap_test_data(Tensor(arr))
+            _cache_summary_tensor_data(test_data)
+            test_writer.record(step=i)
+
+        test_writer.close()
+
+        file_name = os.path.join(tmp_dir, test_writer.event_file_name)
+        reader = SummaryReader(file_name)
+        for _ in range(num_step):
+            event = reader.read_event()
+            assert event.summary.value[0].histogram.count == size
+
+
+def test_histogram_summary_scalar_tensor():
+    """Test histogram summary, input is a scalar tensor."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
+
+        test_data = _wrap_test_data(Tensor(1))
+        _cache_summary_tensor_data(test_data)
+        test_writer.record(step=1)
+        test_writer.close()
+
+        file_name = os.path.join(tmp_dir, test_writer.event_file_name)
+        reader = SummaryReader(file_name)
+        event = reader.read_event()
+        assert event.summary.value[0].histogram.count == 1
+
+
+def test_histogram_summary_empty_tensor():
+    """Test histogram summary, input is an empty tensor."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
+
+        test_data = _wrap_test_data(Tensor([]))
+        _cache_summary_tensor_data(test_data)
+        test_writer.record(step=1)
+        test_writer.close()
+
+        file_name = os.path.join(tmp_dir, test_writer.event_file_name)
+        reader = SummaryReader(file_name)
+        event = reader.read_event()
+        assert event.summary.value[0].histogram.count == 0
+
+
+def test_histogram_summary_same_value():
+    """Test histogram summary, input is an ones tensor."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
+
+        dim1 = 100
+        dim2 = 100
+
+        test_data = _wrap_test_data(Tensor(np.ones([dim1, dim2])))
+        _cache_summary_tensor_data(test_data)
+        test_writer.record(step=1)
+        test_writer.close()
+
+        file_name = os.path.join(tmp_dir, test_writer.event_file_name)
+        reader = SummaryReader(file_name)
+        event = reader.read_event()
+        LOG.debug(event)
+
+        assert len(event.summary.value[0].histogram.buckets) == 1
+
+
+def test_histogram_summary_high_dims():
+    """Test histogram summary, input is a 4-dimension tensor."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
+        dim = 10
+
+        rng = np.random.RandomState(0)
+        tensor_data = rng.normal(size=[dim, dim, dim, dim])
+        test_data = _wrap_test_data(Tensor(tensor_data))
+        _cache_summary_tensor_data(test_data)
+        test_writer.record(step=1)
+        test_writer.close()
+
+        file_name = os.path.join(tmp_dir, test_writer.event_file_name)
+        reader = SummaryReader(file_name)
+        event = reader.read_event()
+        LOG.debug(event)
+
+        assert event.summary.value[0].histogram.count == tensor_data.size
+
+
+def test_histogram_summary_nan_inf():
+    """Test histogram summary, input tensor has nan."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
+
+        dim1 = 100
+        dim2 = 100
+
+        arr = np.ones([dim1, dim2])
+        arr[0][0] = np.nan
+        arr[0][1] = np.inf
+        arr[0][2] = -np.inf
+        test_data = _wrap_test_data(Tensor(arr))
+
+        _cache_summary_tensor_data(test_data)
+        test_writer.record(step=1)
+        test_writer.close()
+
+        file_name = os.path.join(tmp_dir, test_writer.event_file_name)
+        reader = SummaryReader(file_name)
+        event = reader.read_event()
+        LOG.debug(event)
+
+        assert event.summary.value[0].histogram.nan_count == 1
+
+
+def test_histogram_summary_all_nan_inf():
+    """Test histogram summary, input tensor has no valid number."""
+    with tempfile.TemporaryDirectory() as tmp_dir:
+        test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
+
+        test_data = _wrap_test_data(Tensor(np.array([np.nan, np.nan, np.nan, np.inf, -np.inf])))
+        _cache_summary_tensor_data(test_data)
+        test_writer.record(step=1)
+        test_writer.close()
+
+        file_name = os.path.join(tmp_dir, test_writer.event_file_name)
+        reader = SummaryReader(file_name)
+        event = reader.read_event()
+        LOG.debug(event)
+
+        histogram = event.summary.value[0].histogram
+        assert histogram.nan_count == 3
+        assert histogram.pos_inf_count == 1
+        assert histogram.neg_inf_count == 1