enhance embedding error message test=develop (#20246)

* enhance embedding error message test=develop

* enforce .h error test=develop

* fix unittest code test=develop

* Fix fp16 dtype in embedding test=develop

* add import warnings test=develop

paddle/fluid/operators/lookup_table_op.cc

@@ -27,20 +27,28 @@ class LookupTableOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("W"),
+    PADDLE_ENFORCE_EQ(ctx->HasInput("W"), true,
                       "Input(W) of LookupTableOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("Ids"),
+    PADDLE_ENFORCE_EQ(ctx->HasInput("Ids"), true,
                       "Input(Ids) of LookupTableOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
+    PADDLE_ENFORCE_EQ(ctx->HasOutput("Out"), true,
                       "Output(Out) of LookupTableOp should not be null.");
 
     auto table_dims = ctx->GetInputDim("W");
     auto ids_dims = ctx->GetInputDim("Ids");
     int ids_rank = ids_dims.size();
     VLOG(5) << "ids rank is " << ids_rank << std::endl;
-    PADDLE_ENFORCE_EQ(table_dims.size(), 2);
-    PADDLE_ENFORCE_EQ(ids_dims[ids_rank - 1], 1,
-                      "The last dimension of the 'Ids' tensor must be 1.");
+    PADDLE_ENFORCE_EQ(
+        table_dims.size(), 2,
+        "ShapeError: The dimensions of the 'lookup table' must be 2. "
+        "But received lookup table's dimensions = %d, "
+        "lookup table's shape = [%s].",
+        table_dims.size(), table_dims);
+    PADDLE_ENFORCE_EQ(
+        ids_dims[ids_rank - 1], 1,
+        "ShapeError: The last dimensions of the 'Ids' tensor must be 1. "
+        "But received Ids's last dimensions = %d, Ids's shape = [%s].",
+        ids_dims[ids_rank - 1], ids_dims);
 
     auto output_dims =
         framework::vectorize(framework::slice_ddim(ids_dims, 0, ids_rank - 1));

paddle/fluid/operators/lookup_table_op.cu

@@ -158,9 +158,14 @@ class LookupTableGradCUDAKernel : public framework::OpKernel<T> {
       auto *d_table_data = d_table_value->data<T>();
       auto *d_output_data = d_output->data<T>();
       auto d_output_dims = d_output->dims();
-      PADDLE_ENFORCE_EQ(
-          d_table_value->dims(),
-          framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1));
+      auto d_output_dims_2d =
+          framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1);
+      PADDLE_ENFORCE_EQ(d_table_value->dims(), d_output_dims_2d,
+                        "ShapeError: The shape of lookup_table@Grad and "
+                        "output@Grad should be same. "
+                        "But received lookup_table@Grad's shape = [%s], "
+                        "output@Grad's shape = [%s].",
+                        d_table_value->dims(), d_output_dims_2d);
       memory::Copy(gpu_place, d_table_data, gpu_place, d_output_data,
                    d_output->numel() * sizeof(T), stream);
 

paddle/fluid/operators/lookup_table_op.h

@@ -113,9 +113,15 @@ class LookupTableKernel : public framework::OpKernel<T> {
           if (padding_idx != kNoPadding && ids[i] == padding_idx) {
             memset(output + i * row_width, 0, row_width * sizeof(T));
           } else {
-            PADDLE_ENFORCE_GE(ids[i], 0);
+            PADDLE_ENFORCE_GE(
+                ids[i], 0,
+                "Variable value (input) of OP(fluid.layers.embedding) "
+                "expected >= 0. But received %ld",
+                ids[i]);
             auto id_index = table_t.Index(ids[i]);
-            PADDLE_ENFORCE_GE(id_index, 0, "the input key should be exists.");
+            PADDLE_ENFORCE_GE(
+                id_index, 0, "the input key should be exists. But received %d.",
+                id_index);
             blas.VCOPY(row_width, table + id_index * row_width,
                        output + i * row_width);
           }
@@ -180,9 +186,14 @@ class LookupTableGradKernel : public framework::OpKernel<T> {
         auto *d_table_data = d_table_value->data<T>();
 
         auto d_output_dims = d_output->dims();
-        PADDLE_ENFORCE_EQ(
-            d_table_value->dims(),
-            framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1));
+        auto d_output_dims_2d =
+            framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1);
+        PADDLE_ENFORCE_EQ(d_table_value->dims(), d_output_dims_2d,
+                          "ShapeError: The shape of lookup_table@Grad and "
+                          "output@Grad should be same. "
+                          "But received lookup_table@Grad's shape = [%s], "
+                          "output@Grad's shape = [%s].",
+                          d_table_value->dims(), d_output_dims_2d);
         memcpy(d_table_data, d_output_data, sizeof(T) * d_output->numel());
       }
     } else {

paddle/fluid/operators/lookup_table_v2_op.cc

@@ -38,7 +38,12 @@ class LookupTableV2Op : public framework::OperatorWithKernel {
     auto ids_dims = ctx->GetInputDim("Ids");
     int ids_rank = ids_dims.size();
     VLOG(5) << "ids rank is " << ids_rank << std::endl;
-    PADDLE_ENFORCE_EQ(table_dims.size(), 2);
+    PADDLE_ENFORCE_EQ(
+        table_dims.size(), 2,
+        "ShapeError: The dimensions of the 'lookup table' must be 2. "
+        "But received lookup table's dimensions = %d, "
+        "lookup table's shape = [%s].",
+        table_dims.size(), table_dims);
 
     auto output_dims = framework::vectorize(ids_dims);
     output_dims.push_back(table_dims[1]);

paddle/fluid/operators/lookup_table_v2_op.cu

@@ -158,9 +158,14 @@ class LookupTableV2GradCUDAKernel : public framework::OpKernel<T> {
       auto *d_table_data = d_table_value->data<T>();
       auto *d_output_data = d_output->data<T>();
       auto d_output_dims = d_output->dims();
-      PADDLE_ENFORCE_EQ(
-          d_table_value->dims(),
-          framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1));
+      auto d_output_dims_2d =
+          framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1);
+      PADDLE_ENFORCE_EQ(d_table_value->dims(), d_output_dims_2d,
+                        "ShapeError: The shape of lookup_table@Grad and "
+                        "output@Grad should be same. "
+                        "But received lookup_table@Grad's shape = [%s], "
+                        "output@Grad's shape = [%s].",
+                        d_table_value->dims(), d_output_dims_2d);
       memory::Copy(gpu_place, d_table_data, gpu_place, d_output_data,
                    d_output->numel() * sizeof(T), stream);
 

paddle/fluid/operators/lookup_table_v2_op.h

@@ -113,9 +113,15 @@ class LookupTableV2Kernel : public framework::OpKernel<T> {
           if (padding_idx != kNoPadding && ids[i] == padding_idx) {
             memset(output + i * row_width, 0, row_width * sizeof(T));
           } else {
-            PADDLE_ENFORCE_GE(ids[i], 0);
+            PADDLE_ENFORCE_GE(
+                ids[i], 0,
+                "Variable value (input) of OP(fluid.layers.embedding) "
+                "expected >= 0. But received %ld",
+                ids[i]);
             auto id_index = table_t.Index(ids[i]);
-            PADDLE_ENFORCE_GE(id_index, 0, "the input key should be exists.");
+            PADDLE_ENFORCE_GE(
+                id_index, 0, "the input key should be exists. But received %d.",
+                id_index);
             blas.VCOPY(row_width, table + id_index * row_width,
                        output + i * row_width);
           }
@@ -170,9 +176,14 @@ class LookupTableV2GradKernel : public framework::OpKernel<T> {
       auto *d_table_data = d_table_value->data<T>();
 
       auto d_output_dims = d_output->dims();
-      PADDLE_ENFORCE_EQ(
-          d_table_value->dims(),
-          framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1));
+      auto d_output_dims_2d =
+          framework::flatten_to_2d(d_output_dims, d_output_dims.size() - 1);
+      PADDLE_ENFORCE_EQ(d_table_value->dims(), d_output_dims_2d,
+                        "ShapeError: The shape of lookup_table@Grad and "
+                        "output@Grad should be same. "
+                        "But received lookup_table@Grad's shape = [%s], "
+                        "output@Grad's shape = [%s].",
+                        d_table_value->dims(), d_output_dims_2d);
       memcpy(d_table_data, d_output_data, sizeof(T) * d_output->numel());
 
     } else {

python/paddle/fluid/input.py

@@ -13,8 +13,10 @@
 # limitations under the License.
 
 from __future__ import print_function
+import warnings
 from .framework import Variable, in_dygraph_mode
 from .layer_helper import LayerHelper
+from .data_feeder import convert_dtype
 
 __all__ = ['one_hot', 'embedding']
 
@@ -231,6 +233,21 @@ def embedding(input,
     """
 
     helper = LayerHelper('embedding', **locals())
+    if not isinstance(input, Variable):
+        raise TypeError(
+            "The type of 'input' in fluid.embedding must be Variable, but received %s"
+            % (type(input)))
+    if convert_dtype(input.dtype) not in ['int64']:
+        raise TypeError(
+            "The data type of 'input' in fluid.embedding must be int64, but received %s."
+            % (convert_dtype(input.dtype)))
+    if convert_dtype(dtype) in ['float16']:
+        warnings.warn(
+            "The 'dtype' of fluid.embedding only support float16 in GPU now.")
+    if convert_dtype(dtype) not in ['float16', 'float32', 'float64']:
+        raise TypeError(
+            "The 'dtype' of fluid.embedding must be float16, float32 or float64, but received %s."
+            % (convert_dtype(dtype)))
     remote_prefetch = is_sparse and (not is_distributed)
     if remote_prefetch:
         assert is_sparse is True and is_distributed is False

python/paddle/fluid/layers/nn.py

@@ -601,6 +601,21 @@ def embedding(input,
     """
 
     helper = LayerHelper('embedding', **locals())
+    if not isinstance(input, Variable):
+        raise TypeError(
+            "The type of 'input' in layers.embedding must be Variable, but received %s"
+            % (type(input)))
+    if convert_dtype(input.dtype) not in ['int64']:
+        raise TypeError(
+            "The data type of 'input' in layers.embedding must be int64, but received %s."
+            % (convert_dtype(input.dtype)))
+    if convert_dtype(dtype) in ['float16']:
+        warnings.warn(
+            "The 'dtype' of layers.embedding only support float16 in GPU now.")
+    if convert_dtype(dtype) not in ['float16', 'float32', 'float64']:
+        raise TypeError(
+            "The 'dtype' of layers.embedding must be float16, float32 or float64, but received %s."
+            % (convert_dtype(dtype)))
     remote_prefetch = is_sparse and (not is_distributed)
     if remote_prefetch:
         assert is_sparse is True and is_distributed is False

python/paddle/fluid/tests/unittests/test_downpoursgd.py

@@ -40,7 +40,7 @@ class TestListenAndServOp(OpTest):
             print(sys.platform)
             cmd = "wget --no-check-certificate https://pslib.bj.bcebos.com/fleet_desc.prototxt"
             os.system(cmd)
-            x = fluid.layers.data(name='x', shape=[1], dtype='float32')
+            x = fluid.layers.data(name='x', shape=[1], dtype='int64')
             x_emb = fluid.layers.embedding(
                 input=x, size=[1, 2], is_distributed=True)
             y_predict = fluid.layers.fc(input=x_emb, size=1, act=None)
@@ -96,7 +96,7 @@ class TestListenAndServOp(OpTest):
             print(sys.platform)
             cmd = "wget --no-check-certificate https://pslib.bj.bcebos.com/fleet_desc.prototxt"
             os.system(cmd)
-            x = fluid.layers.data(name='x', shape=[1], dtype='float32')
+            x = fluid.layers.data(name='x', shape=[1], dtype='int64')
             x_emb = fluid.layers.embedding(
                 input=x, size=[1, 2], is_distributed=True)
             y_predict = fluid.layers.fc(input=x_emb, size=1, act=None)

python/paddle/fluid/tests/unittests/test_lookup_table_op.py

@@ -20,6 +20,8 @@ from op_test import OpTest
 import paddle.fluid.core as core
 from paddle.fluid.op import Operator
 import paddle.compat as cpt
+import paddle.fluid as fluid
+from paddle.fluid import Program, program_guard
 
 
 class TestLookupTableOp(OpTest):
@@ -150,5 +152,35 @@ class TestLookupTableWithTensorIdsWIsSelectedRows(
             assert (row == result_array[idx]).all()
 
 
+class TestEmbedOpError(OpTest):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            input_data = np.random.randint(0, 10, (4, 1)).astype("int64")
+
+            def test_Variable():
+                # the input type must be Variable
+                fluid.layers.embedding(input=input_data, size=(10, 64))
+
+            self.assertRaises(TypeError, test_Variable)
+
+            def test_input_dtype():
+                # the input dtype must be int64
+                input = fluid.data(name='x', shape=[4, 1], dtype='float32')
+                fluid.layers.embedding(input=input, size=(10, 64))
+
+            self.assertRaises(TypeError, test_input_dtype)
+
+            def test_param_dtype():
+                # dtype must be float32 or float64
+                input2 = fluid.data(name='x2', shape=[4, 1], dtype='int64')
+                fluid.layers.embedding(
+                    input=input2, size=(10, 64), dtype='int64')
+
+            self.assertRaises(TypeError, test_param_dtype)
+
+            input3 = fluid.data(name='x3', shape=[4, 1], dtype='int64')
+            fluid.layers.embedding(input=input3, size=(10, 64), dtype='float16')
+
+
 if __name__ == "__main__":
     unittest.main()

python/paddle/fluid/tests/unittests/test_lookup_table_v2_op.py

@@ -21,6 +21,8 @@ import paddle.fluid.core as core
 import paddle.fluid as fluid
 from paddle.fluid.op import Operator
 import paddle.compat as cpt
+import paddle.fluid as fluid
+from paddle.fluid import Program, program_guard
 
 
 class TestLookupTableOp(OpTest):
@@ -212,5 +214,33 @@ class TestLookupTableApi(unittest.TestCase):
                       return_numpy=False)
 
 
+class TestEmbedOpError(OpTest):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            input_data = np.random.randint(0, 10, (4, 6)).astype("int64")
+
+            def test_Variable():
+                # the input type must be Variable
+                fluid.embedding(input=input_data, size=(10, 64))
+
+            self.assertRaises(TypeError, test_Variable)
+
+            def test_input_dtype():
+                # the input dtype must be int64
+                input = fluid.data(name='x1', shape=[4, 6], dtype='float32')
+                fluid.embedding(input=input, size=(10, 64))
+
+            self.assertRaises(TypeError, test_input_dtype)
+
+            def test_param_dtype():
+                # dtype must be float32 or float64
+                input2 = fluid.data(name='x2', shape=[4, 6], dtype='int64')
+                fluid.embedding(input=input2, size=(10, 64), dtype='int64')
+
+            self.assertRaises(TypeError, test_param_dtype)
+            input3 = fluid.data(name='x3', shape=[4, 6], dtype='int64')
+            fluid.embedding(input=input3, size=(10, 64), dtype='float16')
+
+
 if __name__ == "__main__":
     unittest.main()