mbaret commented on a change in pull request #6303:
URL: https://github.com/apache/incubator-tvm/pull/6303#discussion_r475439237
##########
File path: tests/python/frontend/tflite/test_forward.py
##########
@@ -2652,6 +2652,77 @@ def test_forward_reverse_v2():
_test_reverse_v2((5, 6, 4, 2), np.array([2], dtype='int32'), dtype)
+#######################################################################
+# MATRIX_SET_DIAG
+# ---------------
+
+def _test_matrix_set_diag(input_shape, input_type, quantized=False):
+ """ One iteration of MATRIX_SET_DIAG """
+ with tf.Graph().as_default():
+ diagonal_shape = list(input_shape[:-2])
+ diagonal_shape.append(min(input_shape[-2], input_shape[-1]))
Review comment:
Should the broadcasting case be tested here?
##########
File path: src/relay/op/tensor/transform.cc
##########
@@ -3093,5 +3093,55 @@ RELAY_REGISTER_OP("sparse_to_dense")
.set_attr<FInferCorrectLayout>("FInferCorrectLayout",
ElemwiseArbitraryLayout)
.set_attr<FTVMCompute>("FTVMCompute", SparseToDenseCompute);
+// relay.matrix_set_diag
+bool MatrixSetDiagRel(const Array<Type>& types, int num_inputs, const Attrs&
attrs,
+ const TypeReporter& reporter) {
+ // `types` contains: [input, diagonal, result]
+ CHECK_EQ(types.size(), 3);
+
+ const auto* input = types[0].as<TensorTypeNode>();
+ CHECK(input);
+
+ const auto* diagonal = types[1].as<TensorTypeNode>();
+ CHECK(diagonal);
+
+ int d_ndims = diagonal->shape.size();
+ for (int i = 0; i < d_ndims - 1; i++) {
+ reporter->AssertEQ(input->shape[i], diagonal->shape[i]);
+ }
+ auto min_dim = if_then_else(input->shape[d_ndims - 1] >=
input->shape[d_ndims],
+ input->shape[d_ndims], input->shape[d_ndims -
1]);
Review comment:
Is `if_then_else` appropriate here? Could `a ? x : y` not be used?
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